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‘You do not have to say anything’:
Student Beliefs about the Course of
Events in a Police Interview
Name: Divya Sukumar
Supervisor: Professor David Clarke
Degree: BSc Psychology (Hons)
Student Beliefs about Police Interviews
2
Acknowledgements
I would like to express my deepest gratitude to Professor David Clarke for his endless
guidance, support and most importantly, his sense of humour. His encouragement was an
invaluable source of motivation throughout the project and his unique approach to Psychology will
continue to inspire my further studies.
Student Beliefs about Police Interviews
3
Abstract
Since 1985, police interviews in England have been transformed from psychologically
coercive interrogations to non-confrontational, investigative interviews as guided by the PEACE
model. While legal psychologists have mined a wealth of research to empirically support the
success of individual PEACE model tactics, the fundamentally interactive and dynamic nature of
police interviews has been neglected. The method of sequence analysis, which examines the
succession of events along different pathways, is well suited for the study of interactive processes,
such as police interviews. Thus, this study highlighted the utility of sequence analysis in the
domain of legal psychology by mapping out student beliefs about the patterns of events in police
interviews.
Students were given questionnaires in which they reported the events they believed to
occur in police interviews and importantly, provided the order of the events. Sequential analysis
found that despite the potential influence of fictional dramatizations of police interviews, student
beliefs about the course of events in police interviews were remarkably congruent with the PEACE
model. This was the case regardless of whether students had high or low familiarity with police
interviews. In addition, the study employed the Dawkins method to highlight the utility of
identifying extended sequences of events as well as compared complimentary predictability
analyses to traditional sequence analysis. Ultimately, the set of sequence analysis tools employed
are demonstrated to hold great value for the study of actual police interviews.
Student Beliefs about Police Interviews
4
Introduction
Police Interviews
Police interviews of suspects are key to the process of criminal investigation. The police
interview may resolve unclear issues in the absence of incriminating evidence, direct attention to
other potential suspects or importantly, generate a confession from the suspect (Hartwig, Anders
Granhag, & Vrij, 2005). In the past, police interviews were conducted in accordance with the Reid
Technique, which involves two stages; the behavioural analysis interview to assess whether the
suspect is guilty or innocent of the crime, followed by an accusatory and confrontational
interrogation for suspects deemed ‘guilty’. The interrogation phase has the sole aim of drawing
out the suspect’s confession and essentially requires psychologically manipulative tactics such as
falsely claiming that incriminating evidence exists, deceiving the suspect with fabricated evidence
and maximising the suspect’s fears (Kassin et al., 2010). However, these coercive tactics have been
called into question as recent DNA exonerations have highlighted that approximately 25% of
wrongful convictions are due to false confessions by innocent suspects, for which duress and
coercion are cited as leading causes ("The Innocence Project," 2014). Similarly, experimental
simulations of police interviews have highlighted that students are more likely to falsely confess to
an act such as cheating or crashing a computer if the interviewer holds a guilt-presumptive bias
(Narchet, Meissner, & Russano, 2011), bluffs about having evidence (Perillo & Kassin, 2011) or
presents fabricated evidence (Nash & Wade, 2009).
While surveys of North American police officers reveal that the Reid technique is still very
much in use (Kassin et al., 2007), the Police and Criminal Evidence Act (1985) in England has
introduced an ethical and fairer template of police interviewing known as the PEACE model which
primarily aims to ascertain the truth rather than gain a confession from the suspect. The
inquisitorial PEACE model comprises of five stages; Preparation and Planning, Engagement and
Explaining, gaining an Account, Closure and finally an Evaluation. Initially, police officers are
expected to plan a “route map” (Snook, Eastwood, Stinson, Tedeschini, & House, 2010) as an
outline of all possible events which may occur in the interview, including the suspect’s denial to
speak. The interview then begins with the delivery of the notice of caution and engaging the
suspect in conversation. Next, the interviewer must elicit an account from the suspect without any
interruptions. Any inconsistencies or discrepancies in the suspect’s account may be challenged in a
Student Beliefs about Police Interviews
5
non-aggressive manner before the police officer decides to end the interview. Police officers are
encouraged to self-evaluate at the end of interviews.
The PEACE model prevents interviewers from persuading suspects of unknown guilt
confessing or admitting to a crime they may not have committed, thus avoiding serious
miscarriages of justice such as a wrongful conviction. Moreover, field studies have found that
adherence to the PEACE model enhances interview quality with appropriate delivery of the legally
required notice of caution, rapport building, effective use of pauses and silences and as a result, a
more comprehensive account from the interviewee (Walsh & Bull, 2010) whereas laboratory
studies found that the PEACE model elicited more true confessions and fewer false confessions
compared to the Reid technique (Meissner, Russano, & Narchet, 2010). In particular, two vital
tactics which emerge are rapport building and identifying contradictions in the suspect’s account.
Rapport building has been shown to elicit more accurate information from mock eye-witnesses
(Collins, Lincoln, & Frank, 2002) and is crucial for prompting information from uncooperative
suspects. For this reason, it has been recommended that rapport building tactics such as finding
common ground and meeting the basic needs of the suspect, including water and food, should be
employed early on in the police interview (Kelly, Miller, Redlich, & Kleinman, 2013). Meanwhile,
identifying contradictions in the suspect’s account has been found to successfully prompt
incriminating information in the vast majority of interviews in which it is employed (Leo, 1995). It
is imperative to underscore that police officers have a variety of tactics at hand and must skilfully
and flexibly employ these depending on the suspect’s responses. Thus, despite the success of
certain tactics, police interviews may follow a variety of courses and it is only the start and end of
police interviews which remain relatively uniform (Kelly, et al., 2013).
Crucially, researchers have highlighted that while police officers in England largely follow
the PEACE model which forbids coercive tactics, the use of inappropriate Reid-style tactics
including leading questions and repeating the same question over and over, still occur (Bull &
Soukara, 2010). English police officers appear to resort to such tactics primarily when dealing with
resistant suspects who keep denying their crime (Pearse & Gudjonsson, 1999).
Student Beliefs about Police Interviews
6
Lay Beliefs
In contrast to the large body of research on police interviews, very little is known about the
lay beliefs about police interviews. In North America, the beliefs of potential jurors on the
coerciveness of various police interrogation tactics and their likelihood of eliciting true and false
confessions was examined via questionnaires (Leo & Liu, 2009). The majority of participants
recognized that tactics such as false evidence ploys and threats are psychologically manipulative,
however participants did not believe that the tactics would lead to false confessions which
opposes the conclusions of academics (Drizin & Leo, 2003). As most lay individuals never have any
direct experience with legal and forensic processes, their beliefs often tend to be distinct from
actualities. For instance, even individuals with a good education and interests in criminology have
higher expectations of re-offending than actual rates (Redondo, Luque, & Funes, 1996). Similarly,
English university students with an interest in crime overestimate crime rates (Ainsworth & Moss,
2000).
It is hypothesised that such beliefs about the law and crime are greatly influenced by mass
media (Howitt, 2002). As most citizens have minimal interaction with police forces, their beliefs
and expectations tend to be shaped by crime dramas which have established themselves as one of
the most popular television genres in Western societies (Callanan & Rosenberger, 2011), likely due
to their sensationalist and dramatic portrayal of crime, noble police officers who identify neat
solutions and stylized court trials. Due to the implied reality of such shows, the general population
form their own set of beliefs about the mundane routines of police interviews (Dixon, 2010) and
have even been reported to offer advice to police officers (Huey, 2010).
A candidate explanation of such belief formation is cultivation theory which posits that
information transmitted by television is incorporated into the construction of viewers’ social
‘realities’ (Gerbner & Gross, 1976). In essence, much of what the general public believes about
police stations, courtrooms and operating theatres is learnt from the fictional world of television
drama which offers some insight into the workings of such fascinating institutions. However,
cultivation theory’s predictions that increased television viewing leads to conceptions of the world
which are consistent with the images portrayed on TV has been criticized as too simplistic
(Shanahan & Morgan, 1999) and the correlation between heavy television viewing and distorted
perceptions of crime has not been found in the UK (Gunter, 1987). This may be attributed to a
cultural difference or perhaps, a different media environment.
Student Beliefs about Police Interviews
7
Compatible with cultivation theory’s explanation of lay beliefs about crime is that of the
availability heuristic which suggests that memorable events are often judged as more probable or
frequent (Tversky & Kahneman, 1973). For instance, people overestimate motor vehicle accidents,
homicide and tornadoes as frequent causes of death and in contrast, underestimate the frequency
of causes such as diabetes, stomach cancer and asthma (Lichtenstein, Slovic, Fischhoff, Layman, &
Combs, 1978). A follow up study found that such beliefs correlate with the disproportionate
reporting of dramatic and catastrophic events by newspapers in which diseases are largely
neglected (Combs & Slovic, 1979). This is highly relevant to beliefs about police interviews as
several of the coercive and manipulative tactics now banned in England are imbued with
entertainment value and are potentially more memorable for the general public.
Sequence Analysis
Sequence analysis is a powerful but underused tool tailor made for studying the dynamic
aspects of behaviour and social interaction, for example, siblings fighting or governments
negotiating (Bakeman & Gottman, 1986). It has previously been used to study a range of
behavioural interactions and their temporal structures such as violent incidents at pubs (Beale,
Cox, Clarke, Lawrence, & Leather, 1998), road accidents (Clarke, Ward, & Jones, 1998), sexual
assault (Fossi, Clarke, & Lawrence, 2005) and marital conflict (J. Gottman, Markman, & Notarius,
1977). The complex and dynamic interactions which compromise a police interview are yet to
benefit from the method of sequence analysis. Thus far, police interviews have predominantly
been studied with regard to the various tactics employed by the police officer and how they
correlate with the types of responses produced by the suspect, such as confessions or denials.
Consequently, the sequential patterns underlying the events in a police interview have been
neglected. By examining how the events unfold over time, sequence analysis has the potential to
offer insight into different pathways police interviews can take and their associated outcomes.
Sequence analysis is based on Markov models which were initially used to mathematically
model learning (J. M. Gottman & Roy, 1990) and involves the study of transitions between pairs of
behavioural events, the first of which is referred to as the antecedent and the second of which is
the sequitor. The commonness of the transitions between these events is known as the
transitional frequency and if this is significantly different from the transitional frequency expected
Student Beliefs about Police Interviews
8
by chance, it is likely that the two events are interdependent in that the antecedent is driving the
sequitor. In this manner, probabilistic patterns in the data are uncovered and a rich
characterization of the common sequences of events emerges in the form of a state transition
diagram.
An important characteristic of a sequence is its degree of complexity which is given by its
order. In first order sequences, every event is only dependent on the previous event, in second
order sequences, every event is dependent on the chain of two previous events and so on. Large
amounts of data are required to detect extensive sequences, for example, with the Dawkins’
method in which higher order sequences can be easily identified by locating the most frequent
transition followed by the event most likely to follow or precede that transition and so on (Clarke
& Crossland, 1985).
Finally, it is important to note that thus far in sequence analysis studies, significant
transitions between events have only been used to identify causal relations between the events,
for instance, whether a certain antecedent is causing a sequitor. However, given that the
antecedent has occurred, the most probable event to follow is not necessarily the sequitor which
the antecedent is thought to cause. Forecasting the next event to occur may require a different
analysis. The distinction is essentially between causality, based on contingency statistics, and
predictability, based on conditional probability, an issue which remains unexplored in the domain
of sequence analysis.
Rationale
The present study primarily aims to introduce the method of sequence analysis into the
field of legal psychology. Student beliefs about not only the events which occur in a police
interview but the sequential patterns in which they occur will be examined. Students will be
classified as having high or low familiarity with police interviews as their beliefs about police
interviews may vary as a function of their familiarity. Their responses will then be used to identify
how congruent various lay beliefs of police interview tactics and outcomes are with actual police
interview procedures in England. The utility of a sequential approach for studying psycho-legal
processes will be further highlighted with the Dawkins’ method and an exploratory comparison
between causality and predictability analyses.
Student Beliefs about Police Interviews
9
Method
Participants
Approximately 60 students were approached with an announcement during a lecture and a
response rate of 53 was obtained, out of which 51 questionnaires were usable. In addition, 19
students from other disciplines volunteered to take part in the study, resulting in a convenience
sample of 70. All participants were students at the University of Nottingham, the majority of
whom were undergraduates at the School of Psychology (see Appendix 2). The sample consisted
of 9 males and 61 females with an age range of 19 to 24 years (M= 20.61, SD= 0.73 years). No
financial compensation was provided for participation.
Materials
All participants were given a task pack containing the following documents: an information
sheet explaining the nature and purpose of the study, an informed consent form, the
questionnaire and a debrief sheet (see Appendix 1). The debrief sheet summarized the purpose of
the research and provided contact details of support organisations for any participants who found
the task distressing.
First, the questionnaire required participants to provide their age, gender and course of
study. Next, participants were asked to rate their familiarity with police interviews on a 7-point
Likert scale. While it would have been ideal to compare a group of participants with first-hand
experience of police interviews to a group of participants who had very limited knowledge of
police interviews, recruiting actual suspects or convicted offenders was not within the scope of
this project. Thus, as a methodological compromise, participants’ relative familiarity with police
interviews along with their primary source of knowledge on police interviews was assessed. In
addition, a number of incidental 7-point Likert scales were included to assess participants’
attitudes to offender treatment, their beliefs about the causal role of genetics in criminal
behaviour and the success of police officers in upholding the law. For these three measures, the
wording was varied so that participants could not plausibly provide the same rating on all three
scales.
Student Beliefs about Police Interviews
10
Following this, the questionnaire presented participants with an exemplary list of events
which may occur when a student attends a lecture. Some of these events were ticked to indicate
that they do occur and these were numbered in an appropriate order to guide participants with
the main task. Importantly, there were three number columns to give participants the option to
include an event multiple times if necessary. To demonstrate this option, one of the events in the
example list was numbered twice. The questionnaire then requested participants to imagine a
single police interview, with the phrase ‘a single police interview’ underlined to emphasize that
participants should not imagine an aggregated version of several police interviews. The task sheet
then presented 37 potential events which may occur during a police interview in a randomized
order. The initial event of the notice of caution, and the potential final events of the suspect
admitting to part of the crime, confessing to the full crime, denying the crime or providing
information about previous offenses or co-suspects were taken from an observational study of
real police interviews in different police stations in England (Softley, Brown, & Britain, 1980). The
remaining 32 events were common police interview techniques taken from a total of 71
techniques described in Kelly et al. (2013). Only 32 techniques were included as the remaining
techniques were too similar or they took place before, after or during the interview as a whole. As
an additional validation check, an ex-chief inspector from Nottinghamshire provided feedback on
the 37 events, commenting that some events such as the notice of caution were realistic while
others such as presenting fabricated evidence were far-fetched. Moreover, it was deemed that in
reality, “most suspect interviews are somewhat mundane” as are the events in them.
Identically to the example list, a left-hand column was provided to tick the events which
participants believed to occur in police interviews and three number columns on the right hand
side were provided for participants to order the events appropriately. None of the events included
technical jargon, with the exception of the notice of caution for which a footnote quoting the
official English caution was provided. The use of the footnote was to ensure that none of the
events were particularly lengthy and attention-grabbing as this may imply its importance to
participants. In a similar vein, all the events were fitted on a single page to prevent participants
from being biased to events on the initial or later pages.
Student Beliefs about Police Interviews
11
Procedure
Most participants were approached during a lecture with an announcement explaining the
nature of the task with a few participants volunteering outside of lecture time to complete the
task. Participants were allowed to decline to take part in the study, however if they chose to take
part, they returned the task pack to the experimenter immediately after completing the task. To
ensure anonymity and confidentiality of data, all consent forms were separated from the task
packs prior to viewing or processing the response data.
Participants, after signing the consent form, followed instructions and completed the
aforementioned questionnaire. Participants were debriefed and thanked. The whole procedure
lasted no longer than 15 minutes.
Results
Sample Characteristics
Participants’ familiarity with police interviews ranged from 1 (‘No idea at all’) to 7 (‘First-
hand experience’) with a mean of 3.30 (SD = 1.468). Participants who selected 4 or above on the
familiarity scale were placed in the High Familiarity condition while participants who selected 3 or
below on the familiarity scale were placed in the Low Familiarity condition. Television was most
frequently cited as one of the primary sources of information on police interviews with 51
participants either referring to television alone or in combination with, for example, detective
stories (see Appendix 3). For the remaining 7-point scales, participants tended to slightly disagree
that offender treatment in the UK is too harsh (M= 2.96, SD= 1.069) and that criminal behaviour is
largely influenced by genetic factors (M= 3.24, SD= 1.367), while attitudes towards police officers
upholding the law were neutral (M= 3.94, SD=1.190). There was no significant difference between
the responses on these three scales for the High Familiarity and Low Familiarity conditions
(p<0.05).
Student Beliefs about Police Interviews
12
Details of Frequency Analysis
Each event was assigned a unique two letter code (see Appendix 4) and using this coding
system, participants’ responses were arranged as data strings using Microsoft Excel and Word (see
Appendices 5 & 6 for all data strings). All event frequencies, which were defined as the number of
times a participant indicated that an event would occur during a police interview, were
determined using Microsoft Word.
Event frequencies for the complete dataset and the High and Low Familiarity conditions
are displayed in Figures 1-3.
Student Beliefs about Police Interviews
13
Figure 1. Graph displaying event frequencies for all participants.
0 20 40 60 80
Accuse suspect of being someone else
Touch suspect in a friendly manner
Flatter suspect
Insult suspect
Confront suspect with fabricated evidence
Move interrogation from a formal to a neutral setting
Present self as someone other than the interrogator
Identify and exaggerate fears
Instil hopelessness in suspect
Morally rationalize alleged crime
Make angry/frustrated/impatient gestures
Dismiss suspect's evidence
Bluff suspect about having evidence
Threaten suspect
Misconstrue suspect's words
Move interrogation from a neutral to formal setting
Use polygraphs/physiological measures
Ask a series of questions without allowing suspect to answer
Reduce fear
Use deception
Employ another interrogator (good cop/bad cop)
Directly accuse suspect
Find common ground
Suspect gives information on previous offenses/co-suspects
Suspect's confession to full crime
Stare at suspect in silence
Identify and meet basic needs
Confront suspect without insulting
Suspect's admission to part of the crime
Notice of caution
Show photos from witnesses
Offer rewards for cooperation
Identify contradictions in suspect's story
Reveal evidence to suspect
Repeat question over and over again
Ask unexpected questions
Suspect's denial
Even
t
Frequency
Student Beliefs about Police Interviews
14
Figure 2. Graph displaying event frequencies for high familiarity participants.
0 5 10 15 20 25
Flatter suspect
Instil hopelessness in suspect
Accuse suspect of being someone else
Identify and exaggerate fears
Move interrogation from a formal to a neutral setting
Touch suspect in a friendly manner
Insult suspect
Bluff suspect about having evidence
Present self as someone other than the interrogator
Confront suspect with fabricated evidence
Morally rationalize alleged crime
Threaten suspect
Make angry/frustrated/impatient gestures
Dismiss suspect's evidence
Move interrogation from a neutral to formal setting
Ask a series of questions without allowing suspect to answer
Directly accuse suspect
Reduce fear
Misconstrue suspect's words
Use polygraphs/physiological measures
Use deception
Employ another interrogator (good cop/bad cop)
Find common ground
Suspect's confession to full crime
Stare at suspect in silence
Suspect gives information on previous offenses or co-suspects
Suspect's admission to part of the crime
Notice of caution
Identify contradictions in suspect's story
Ask unexpected questions
Identify and meet basic needs
Reveal evidence to suspect
Repeat question over and over again
Show photos from witnesses
Offer rewards for cooperation
Confront suspect without insulting
Suspect's denial
Even
tFrequency
Student Beliefs about Police Interviews
15
Figure 3. Graph displaying event frequencies for low familiarity participants.
0 10 20 30 40 50
Accuse suspect of being someone else
Touch suspect in a friendly manner
Insult suspect
Confront suspect with fabricated evidence
Flatter suspect
Present self as someone other than the interrogator
Move interrogation from a formal to a neutral setting
Morally rationalize alleged crime
Make angry/frustrated/impatient gestures
Misconstrue suspect's words
Identify and exaggerate fears
Use polygraphs/physiological measures
Instil hopelessness in suspect
Move interrogation from a neutral to formal setting
Dismiss suspect's evidence
Threaten suspect
Ask a series of questions without allowing suspect to answer
Use deception
Bluff suspect about having evidence
Employ another interrogator (good cop/bad cop)
Reduce fear
Find common ground
Suspect gives information on previous offenses or co-suspects
Directly accuse suspect
Confront suspect without insulting
Suspect's confession to full crime
Identify and meet basic needs
Stare at suspect in silence
Show photos from witnesses
Suspect's admission to part of the crime
Offer rewards for cooperation
Notice of caution
Reveal evidence to suspect
Identify contradictions in suspect's story
Repeat question over and over again
Ask unexpected questions
Suspect's denial
Even
t
Frequency
Student Beliefs about Police Interviews
16
Figure 4 presents event frequencies as a proportion of the total frequency for each
familiarity condition in order to facilitate comparison between the two familiarity conditions.
Figure 4. Graph displaying proportional event frequencies for high and low familiarity conditions. (Events
are shown in order of overall frequency for both familiarity conditions.)
Student Beliefs about Police Interviews
17
Frequency Discussion
It is interesting to note from Figure 1 that dramatic, psychologically coercive events such as
instilling hopelessness in suspect, identifying and exaggerating fears and insulting suspect which
are not only commonplace in fiction and media but also quite memorable appear to have the
lowest frequencies. In contrast, events such as the notice of caution, identifying and meeting
basic needs and staring at the suspect in silence which are routine police interview events but
could be argued to lack entertainment value have higher frequencies. This pattern of results is
maintained in both the high and low familiarity conditions as demonstrated by Figures 2-3.
Figure 4 highlights that very similar patterns of event frequencies emerge for both high and
low familiarity participants. For some events, the proportional frequency may appear to vary as a
function of familiarity, for instance, the events of the police interviewer confronting the suspect
without insulting, instilling hopelessness in the suspect or the suspect providing information about
previous offenses or co-suspects. However, the difference in proportions test found that the
frequencies for these three events are not significantly different for high and low familiarity
participants (p<0.05).
Classification
Conducting a sequence analysis on 37 events would require an unnecessarily large matrix
of 1,369 cells. Hence events with a frequency of 11-20 were reclassified as a Medium Frequency
event (with the code MF) while events with a frequency of 10 or below were reclassified as a Low
Frequency Event (with the code LF). As a result, the 17 events shown in Table 1 remained for
sequence analysis.
Student Beliefs about Police Interviews
18
Table 1. Table displaying the events, with respective codes and frequencies, used for sequence analysis.
Event Code Frequency
Suspect's denial AA 63
Ask unexpected questions AE 46
Repeat question over and over again AH 45
Reveal evidence to suspect AG 43
Offer rewards for cooperation AO 41
Identify contradictions in suspect's story BD 41
Notice of caution AB 39
Show photos from witnesses AI 39
Suspect's admission to part of the crime BE 36
Identify and meet basic needs AP 35
Confront suspect without insulting AY 35
Stare at suspect in silence AF 33
Suspect's confession to full crime BC 29
Suspect provides information about previous offenses or co-suspects AW 25
Find common ground AR 24
Medium frequency event MF 170
Low frequency event LF 69
Next, the frequency of transitions between each of these events was ascertained from the
data strings using Microsoft Word to produce a transitional frequency matrix for the complete
dataset (see Appendix 7). However, the numbers were quite sparse across the matrix and failed to
meet the criterion for an overall chi-squared test for which less than 20% of the cells must have an
expected count of less than 5.
Student Beliefs about Police Interviews
19
Cluster Analysis
In order to further collapse the event categories (excluding the MF and LF events) to meet
the aforementioned chi-squared criterion, single linkage cluster (SLINK) analysis was used. SLINK
analysis, independently suggested by both Sneath (1957) and McQuitty (1957), is a method of
hierarchical clustering in which initially, the two individual events sharing the highest similarity are
linked to each other to form a cluster. One by one, each of the remaining events is then linked to
another event based on their similarity until eventually all the events are linked in one overarching
cluster. For this study, 'similarity' in sequential terms (or more strictly the commutation or
swapablility) of two events, such as A and B, was calculated by taking the frequencies with which A
followed another event (X) and B followed X, together with the frequencies with which A preceded
X and B preceded X, and correlating the A values with the B values over all values of X. Essentially,
if two events frequently followed the same antecedents and frequently preceded the same
sequitors, then the two events could be considered highly similar. All correlations are displayed in
Table 2.
Table 2. Similarity table showing correlations between transition frequencies of pairs of events.
AA AB AE AF AG AH AI AO AP AR AW AY BC BD BE
AA 1.000
AB 0.175 1.000
AE 0.389 0.331 1.000
AF 0.543 0.205 0.260 1.000
AG 0.270 0.122 0.547 0.272 1.000
AH 0.206 0.082 0.354 0.265 0.490 1.000
AI 0.280 -0.104 0.185 0.404 0.058 0.453 1.000
AO 0.130 0.082 0.479 -0.132 0.292 0.283 0.269 1.000
AP 0.450 0.243 0.282 0.407 0.092 0.060 0.095 0.254 1.000
AR 0.152 0.126 0.337 0.268 0.241 0.432 0.379 0.389 0.211 1.000
AW 0.048 -0.002 0.269 -0.075 0.247 0.196 0.023 0.374 0.053 0.271 1.000
AY 0.251 -0.030 0.555 0.292 0.330 0.363 0.329 0.606 0.345 0.390 0.413 1.000
BC -0.194 -0.100 -0.140 -0.243 -0.109 -0.019 0.064 0.063 -0.111 -0.024 0.140 -0.048 1.000
BD 0.007 -0.094 0.334 0.027 0.267 0.369 0.258 0.437 0.004 0.325 0.430 0.489 0.155 1.000
BE 0.089 -0.082 0.252 -0.061 0.287 0.205 0.206 0.423 0.097 0.267 0.444 0.530 0.425 0.486 1.000
The similarity table was then used to create a dendogram with Microsoft Paint, illustrated
in Figure 5, which diagrammatically demonstrates the linkages and clusters of events.
Student Beliefs about Police Interviews
20
Figure 5. Dendogram illustrating events clustered by the correlations between their transition frequencies.
Using the dendogram, the events were collapsed into only three categories; event AB as a
cluster, events AF, AA and AP which were recoded as cluster FP and the remaining events as
cluster RC. The aforementioned criterion for the chi-squared test was met and it was revealed that
there was a sequential structure in the data worthy of further investigation (x2(36) = 1293.6, p <
0.005), see Appendix 8.
Student Beliefs about Police Interviews
21
Sequence Analysis
For the sequence analysis, the original events prior to the SLINK analysis, were used in
order to attain sufficient detail. Using SPSS, transitional frequency matrices, which included
standardized residuals, were produced for the complete dataset, high familiarity condition and
low familiarity condition (see Appendix 9). To identify which transitions were occurring at
frequencies higher than expected at chance level, a critical value was calculated for comparison
using Equation 1, (Colgan & Smith, 1978).
= √𝐶ℎ𝑖 𝑆𝑞𝑢𝑎𝑟𝑒 𝑐𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑣𝑎𝑙𝑢𝑒
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑒𝑙𝑙𝑠 𝑖𝑛 𝑡𝑎𝑏𝑙𝑒
Equation 1. For calculating a critical value to compare standardized residuals to.
The critical value was 1.008 for the complete dataset, high familiarity and low familiarity
conditions. However this was treated as a lower bound and a more stringent critical value of 2.000
was used to compare standardized residuals to. In addition to transitions having a standardized
residual above the critical value of 2.000, the researcher added a further criterion of transitions
having a raw occurrence of >5 for the complete dataset and >2 for the high and low familiarity
conditions. As such, only the more important transitions were included in the maps.
Using yEd Graph Editor (yEd Graph Editor, version 3.11, 2014), state transition diagrams
were produced for all conditions as highlighted by Figures 5, 7 and 8. Figure 6 is an illustration of
what the low frequency and medium frequency events in the complete dataset represent.
Student Beliefs about Police Interviews
23
Figure 6. State transition diagram unpacking low and medium frequency events (Numbers refer to raw
occurrences).
Student Beliefs about Police Interviews
24
Figure 7. State transition diagram for high familiarity condition.
Student Beliefs about Police Interviews
25
Figure 8. State transition diagram for low familiarity condition.
Student Beliefs about Police Interviews
26
Sequence Analysis Discussion
Overall, Figures 5, 7-8 highlight that all participants were well aware that police interviews
typically start with the notice of caution, which is also a legal requirement in England.
Interestingly, the suspect’s denial which had been included as a potential outcome of the
interview was not only the most frequent event across conditions but also consistently appeared
as one of the initial events following the notice of caution. Meanwhile the alternative outcomes of
confession or partial admission are closely clustered to the end of the interview. This implies that
students believe that most suspects begin by denying their part in the alleged crime but that
ultimately, police interviews only end when a confession or at minimum, an admission is elicited.
There are two possible explanations of this finding; either students hold a guilt presumptive bias
and are under the impression that despite initial denials, suspects called in for police interviews
are guilty of the crime in question and will eventually confess or alternatively, students are aware
of the high rate of false confessions and believe that police investigators will only terminate an
interview when a confession is elicited. However, it is unlikely that students were aware of false
confessions as these tend to be associated with psychologically manipulative techniques, such as
threats or bluffing, whereas students have mostly associated the ethically approved technique of
identifying contradictions in the suspect’s story as precipitating the suspect’s confession or
admission.
In addition, as underscored by Figure 5, 7 and 8, there are relatively few or no transitions
linking the cluster of final events, including the suspect’s admission, confession and ultimately the
end of the interview, with the remaining events which suggests that students believe that there
are a variety of pathways, as opposed to a single successful route, to reach the interview’s
conclusion.
Finally, a rapport building pathway emerges across conditions in which the suspect’s basic
needs are met and the suspect is engaged in conversation by finding common ground, as
illustrated on the left of all the state transition diagrams.
Student Beliefs about Police Interviews
27
Comparison between familiarity conditions
The state transition diagrams in Figures 9-11 illustrate the common and unique transitions in
the two familiarity conditions.
Figure 9. State transition diagram with transitions common to both familiarity conditions.
Student Beliefs about Police Interviews
28
Figure 10. State transition diagram with transitions only found in high familiarity condition.
Student Beliefs about Police Interviews
29
Figure 11. State transition diagram with transitions only found in low familiarity condition.
Student Beliefs about Police Interviews
30
While Figure 9 underscores that a number of event transitions are common to both high
and low familiarity conditions, Figures 10-11 exemplify the key differences between the two
conditions. For example, high familiarity students seem to believe that the police interview does
not always begin with the notice of caution and may instead begin with identifying and meeting a
suspect’s basic needs. This may occur if a police officer chooses not to closely follow the PEACE
model and legal requirements in England. Further, high familiarity students believe that the
suspect’s denial is a recurring event during the interview as highlighted by its multiple transitions
in Figure 10.
Conversely, it is clear from Figure 11 that low familiarity students hold the belief that even
a suspect’s partial admission is sufficient to terminate a police interview unlike high familiarity
students who believe that the only pathway to the interview’s end is via a full confession by the
suspect. Another key difference is that low familiarity students believe that even the act of
revealing evidence will be effective in obtaining a full confession whereas for high familiarity
students, the pathway between revealing evidence and a full confession requires several other
steps. Likewise, confronting the suspect is very closely linked to the final events of confession and
admission for low familiarity students. This may reflect low familiarity students believing in less
resistant suspects and possibly shorter police interviews.
A limitation of the method of sequence analysis used thus far is that first order sequences,
involving transitions only between pairs of events, were used to generate maps which create the
impression that longer chains of events have been identified in the data. These longer chains of
events may or may not exist.
Dawkins’ method
In order to deal with the limitation of using first-order sequences to create maps with
lengthy chains of events, the more rigorous and elaborate Dawkins’ method of sequence analysis
was used to detect extended chains of events in the data (Clarke & Crossland, 1985). This involves
identifying the transition with the highest frequency and then finding the event which is most
likely to follow or precede this transition and so on. As this is a data hungry method, it was only
used on the overall dataset and the resulting transitional frequency matrices are attached in
Student Beliefs about Police Interviews
31
Appendix 10. Two exemplary sequences are shown below with numbers indicating the
frequencies:
(((ST – AB24) AP8) AE2)
Start-> Notice of caution -> Identify and meet basic needs.
(AO2 (AW2 (BE6 (BC25 – EN))))
Offer rewards for cooperation -> Suspect provides information on previous crimes/co-suspects ->
Suspect’s admission to part of the crime -> Suspect’s confession to full crime -> End.
The Dawkins method of sequence analysis is in line with previous findings for the complete
dataset as the two extended chains found map well onto the pathways illustrated in Figure 5.
Moreover, it highlights that according to students, one of the more likely pathways to the
suspect’s admission and confession is through offering rewards for cooperation which was not
revealed in the previous analyses. Of interest is that the two extended chains of events which
emerged (excluding the MF and LF events) with the Dawkins method involved the start and end of
the police interview implying that those are believed to be the most predictable stages.
Predictability Analysis
Traditionally in sequence analysis, row and column totals of transitional frequency matrices
are used to produce an expected frequency for each transition and if the actual frequency is
significantly different from this, it may be inferred that the first event is in some sense causing the
second event. In contrast to such causality analysis, conditional probability can be used to
forecast the following event in a sequence given the current event. The row percentages in the
transitional frequency matrices (see Appendix 9) can be used for the latter analysis. In this study,
there were primarily two instances where the two types of analyses produced different results.
In the low familiarity dataset, traditional sequence analysis uncovered a significant
transition from offering rewards for cooperation to finding common ground however with the
predictability analysis, both suspect’s denial and the end of the interview are equally likely to
follow at 12.5%. Similarly, although there is a significant transition between revealing evidence to
Student Beliefs about Police Interviews
32
suspect and suspect’s full confession, revealing evidence may be followed by the suspect’s denial
or repeating question over and over again at an equal probability of 11.1%.
In both instances, the predictability analysis highlights that even if traditional sequence
analysis finds a causal link between two events, it may not be sufficient to predict the second
event. This approach is particularly useful for analysing actual police interviews where the
likelihood of continued denial by the suspect may be underestimated by traditional sequence
analysis, as in this study.
General Discussion
The present study aimed to introduce the powerful tool of sequence analysis into the field
of legal psychology. Student beliefs about the patterns of events which unfold in police interviews
and how these relate to the final outcome were examined. Remarkably, both high and low
familiarity students held several accurate beliefs about the conduct of police interviews in
England, in accordance with the PEACE model. The Reid-style techniques which were previously in
use in England such as bluffing, presenting fabricated evidence and maximising suspects’ fears, all
of which are associated with false confessions (Narchet, et al., 2011; Nash & Wade, 2009; Perillo &
Kassin, 2011), were rarely cited as events which could occur in a police interview. Meanwhile, the
resulting sequences of police interview events closely resembled what is recommended by the
PEACE model with initial rapport building followed by a number of non-aggressive tactics such as
staring at the suspect in silence and the highly successful tactic of identifying contradictions in the
suspect’s account. Thus, rapport-building and identifying contradictions in the suspect’s story, two
fundamental ways of dealing with resistant suspects in police interviews, as highlighted both by
field and laboratory studies (Collins, et al., 2002; Kelly, et al., 2013; Leo, 1995), are correspondingly
given importance by students. Interestingly, the act of repeating questions, an inappropriate tactic
which is nevertheless still used by police officers in England (Bull & Soukara, 2010; Pearse &
Gudjonsson, 1999), is also reported as a central event in police interviews by students.
The use of the Dawkins method to identify extended sequences of events further
supported the accuracy of student beliefs as the two chains of events which emerged were
located at the beginning and end of the interview. This suggested that the least variable and thus
Student Beliefs about Police Interviews
33
most predictable stages of the police interview were the start and end while the traditional
sequence analysis method highlighted that there was no single pathway to the end of the
interview, implying that the police interview as a whole could follow a number of routes. Once
again, the complex and flexible nature of the police interview, apart from its initial and final stages
has been emphasized in the literature (Kelly, et al., 2013).
The only notable departure in student beliefs from actuality, is the close association
between suspect confessions or admissions and the end of the interview in contrast to suspect
denials which are rarely believed to conclude a police interview. This is distinct from the guidelines
of the PEACE model in which no assumptions about the suspect’s guilt should be made, allowing a
police officer to end the interview even if the suspect continues to claim their innocence (Snook,
et al., 2010). Hence, students either believe that police officers predominantly question guilty
suspects and are determined to gain a true confession or they believe that some of the final
confessions are false. The latter is less likely, particularly with the non-confrontational tactics
found in the sequences as lay individuals rarely believe false confessions occur even with
psychologically coercive tactics (Leo & Liu, 2009).
In terms of familiarity, the key difference between high and low familiarity students was
their beliefs about a suspect’s resistance during a police interview. Low familiarity students
believed that shorter sequences of events, such as revealing evidence or confronting the suspect,
could directly drive a suspect’s confession whereas high familiarity students believed in lengthier
pathways to the suspect’s confession, often involving recurring denials by the suspect.
These findings of accurate beliefs are divergent from related studies in the literature in
which lay beliefs are distinct from actual crime statistics (Ainsworth & Moss, 2000; Redondo, et al.,
1996). Despite the majority of participants citing television and other fictional media, such as
detective stories, as their primary sources of information on police interviews, their beliefs about
the sequential patterns in a police interview are more consistent with actuality than what would
be expected from the dramatic and sensationalist portrayals in the mass media (Callanan &
Rosenberger, 2011). While this study did not intend to test the predictions of cultivation theory
and the availability heuristic, the results are not necessarily incompatible with the two theoretical
frameworks which suggest that recurrent images in the media are likely to play a significant role in
shaping lay beliefs. It is possible that the media environment in England is different as previously
suggested (Gunter, 1987) and that it simply includes more accurate depictions of police
Student Beliefs about Police Interviews
34
interviews. Further, although students reported television as their primary source of information,
it is likely that they were influenced by other reliable sources, such as their course of study since
the majority of the participants were Psychology students and are likely to have covered police
interviews in class.
This study also explored the empirical difference between causality and predictability
analyses in sequence analysis. For the most part, significant transitions between two events as
identified by the traditional sequence analysis, in which the first event appears to be causing a
second event, produced similar results to the conditional probability findings, in which the second
event is most likely to follow the first event. However, a few discrepancies between the two
analyses arose, primarily involving the high likelihood of events being followed by the suspect’s
denial even if those events were found to ‘cause’ another event such as the suspect’s full
confession. In essence, the causal links found between events were not sufficient to forecast the
following event for which conditional probabilities are more appropriate.
The practical implications of the present study centre on how much a sequential approach
has to offer for legal psychology. By applying this analytical tool to student beliefs about police
interviews, previously inaccessible levels of information have been acquired about the interactive
and dynamic nature of police interviews. This has paved the way for future avenues of research
involving sequence analysis of actual police interviews in which various tactics and the outcomes
they lead to may be identified. Common patterns may emerge in the data, for example, the most
frequent extended chain of events which leads to a suspect’s full confession as revealed by the
Dawkins method in this study. Further, similarly to this study’s comparison between high and low
familiarity students’ beliefs, the datasets for actual police interviews can be divided according to
suspects’ demographics and characteristics in order to compare whether different sequences
emerge depending on contextual variables. Moreover, the exploratory comparison between
causality and predictability analyses in this study has spotlighted how useful a complementary
analysis of conditional probabilities can be. For instance, it may expose the suspect’s tendency to
be more resistant in response to certain tactics. Therefore, while the police officer may expect
that revealing evidence will drive the suspect to confess, an equally valid prediction may be the
reverse outcome; the suspect’s denial. Ultimately, the family of sequence analysis methodologies
is highly suitable for preparing police officers in the Preparation and Planning stage of the PEACE
model which encourages the use of “route map[s]” (Snook, et al., 2010). State transition diagrams,
Student Beliefs about Police Interviews
35
such as those created in this study, would enable police officers to familiarize themselves with all
possible directions the interview may take and the likely tactics which could steer the interview in
a more desirable direction.
This study is not without its limitations as the method of sequence analysis is data-hungry
and thus requires extensive data collection in order to identify more complicated patterns of social
interaction. For this reason, the present study primarily identified simple pairwise patterns which
were then arranged in sequences and even the extended sequences identified by the
sophisticated Dawkins method were relatively short. Therefore, future researchers may want to
gather larger data sets in order to unveil more intricate patterns of events in police interviews.
Another limitation is that sequence analysis is a frequency driven method, in that its goal is to find
common ways in which events unfold. While this may be appropriate for the beliefs of students
about police interviews, the study of actual police interviews may benefit from a study of the rarer
and possibly more interesting sequences of events which may transpire for which alternative
sequential approaches may be more suitable.
Despite these limitations, the study has shown that student beliefs about the sequences of
behavioural events in police interviews are surprisingly congruent with policy in England as
opposed to being distorted by fictional portrayals of police interviews. Critically, the study has
presented legal psychology with a novel method of studying police interviews which captures its
fundamentally interactive and dynamic nature.
Word Count: 6669
Student Beliefs about Police Interviews
36
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Student Beliefs about Police Interviews
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Appendix 1: Task Pack
University of Nottingham
School of Psychology
Information Sheet
Research Project on Student Beliefs about Police Interviews
Researchers: Divya Sukumar, Professor David Clarke
Contact Details: [email protected]
This is an invitation to take part in a research study on students’ beliefs about police interviews.
The reason you have been approached is because you are a student at the University of Nottingham.
Before you decide if you wish to take part, it is important for you to understand why the research is being
done and what it will involve. Please take time to read the following information carefully.
If you participate, you will be given a list of possible events from police interviews. You will have to imagine
a single police interview, decide which of the events will occur in it and then put them in the order in which
you believe they would occur. The whole procedure will last approximately 15 minutes.
Participation in this study is totally voluntary and you are under no obligation to take part. Thinking about
the events in a police interview may be distressful, particularly if you or someone you know has been
through a police interview. Therefore if this topic may evoke distress or discomfort, please do not
participate in this study. If you do choose to participate in this study, remember that you are free to
withdraw at any point before or during the study. Your responses will be anonymous and all data collected
will be kept confidential and used for research purposes only.
If you have any questions or concerns please don’t hesitate to ask now. We can also be contacted after
your participation at the above address.
Thank you for your time.
Student Beliefs about Police Interviews
40
CONSENT FORM
Student Beliefs about Police Interviews
Investigators: Divya Sukumar, Professor David Clarke
School of Psychology, University of Nottingham
The participant should complete the whole of this sheet himself/herself. Please cross out as necessary
Have you read and understood the participant information sheet YES/NO
Have you had the opportunity to ask questions and discuss the study YES/NO
Have all the questions been answered satisfactorily YES/NO
Have you received enough information about the study YES/NO
Do you understand that you are free to withdraw from the study:
at any time YES/NO
without having to give a reason YES/NO
Do you agree to take part in the study YES/NO
“This study has been explained to me to my satisfaction, and I agree to take part. I understand that I am free to withdraw at any time.”
Signature of the Participant: Date:
Name (in block capitals)
I have explained the study to the above participant and he/she has agreed to take part.
Signature of researcher Date
Student Beliefs about Police Interviews
41
Task
Please provide the following personal information:
Age: …………………………
Gender: ………………………
Course of Study: …………………………………………………………………
It would be helpful if you answer the following questions:
How much do you know about what goes on during police interviews? (Please circle the
appropriate answer)
1 2 3 4 5 6 7
No idea First-hand
at all experience
Please state your main source of information on police interviews (e.g. television programs, first-
hand experience, detective stories, descriptions by friends):
……………………………………………………………………………………
Do you agree with the following statements? (Please circle the appropriate answer)
‘I think the treatment of offenders by the criminal justice system in this country is too harsh.’
1 2 3 4 5 6 7
Strongly Disagree Strongly Agree
‘Criminal behaviour is largely influenced by genetic factors.’
1 2 3 4 5 6 7
Strongly Disagree Strongly Agree
‘Police officers do an excellent job of upholding the law.’
1 2 3 4 5 6 7
Strongly Disagree Strongly Agree
Student Beliefs about Police Interviews
42
Information: Now you will see a list of possible events in police interviews. Please
imagine a single police interview and decide which of the events would occur in it.
First, tick the events which you believe occur in the left hand column. The next stage
is to number those events in the order you believe them to occur using the
‘Number’ column on the right. If you believe some events occur more than once in a
police interview, number those events again in the additional ‘Number’ columns.
Example: Attending a lecture
To give you an example of how your form should look like, here is an imaginary
example from a completely different domain of behaviour.
Item Number
Student greets friends 2 5
Student picks up a handout
Student enters lecture theatre 1
Lecturer enters 3
Student takes seat at the front
Student takes seat at the back 4
Student Beliefs about Police Interviews
43
Now, using the example as a guide, do the same for the following list of events.
Item Number
Suspect’s denial
Notice of caution1
Use polygraphs/physiological measures
Touch suspect in a friendly manner
Ask unexpected questions
Stare at suspect in silence
Reveal evidence to suspect
Repeat question over and over again
Show photos from witnesses
Instil hopelessness in suspect
Insult suspect
Directly accuse suspect
Use deception
Accuse suspect of being someone else
Offer rewards for co-operation
Identify and meet basic needs
Bluff suspect about having evidence
Find common ground
Morally rationalize alleged crime
Employ another interrogator (good cop/bad cop)
Threaten suspect
Flatter suspect
Suspect provides information about previous offences or co-suspects
Present self as someone other than the interrogator
Confront suspect without insulting
Reduce fear
Misconstrue suspect’s words
Make angry/frustrated/impatient gestures
Suspect’s confession to full crime
Identify contradictions in suspect’s story
Suspect’s admission to part of the crime
Identify and exaggerate fears
Move interrogation from a neutral to formal setting
Dismiss suspect’s evidence
Confront suspect with fabricated evidence
Move interrogation from a formal to neutral setting
Ask a series of questions without allowing suspect to answer
Thank you for taking part in this study.
1 “You do not have to say anything. But it may harm your defence if you do not mention when questioned something which you later rely on in court. Anything you do say may be given in evidence.”
Student Beliefs about Police Interviews
44
Debrief Sheet
Thank you for taking part in this study. Your involvement has been of great value in this
project.
This study intends to map out the sequence of events which students believe to occur in a
police interview. All responses submitted will be analysed collectively and the data will remain
anonymous and confidential at all times. This information is for research purposes only; it is not
the intention of this study to pass judgement on any of the opinions expressed by participants and
the collected responses will only be viewed by myself and my supervisor.
Police interviews can be a distressing topic. If you would like to talk to someone about your
own or someone else’s experience with police interviews, please make use of the phone numbers
below:
Victim Support: 0845 3030 900
Confidential and independent helpline offering emotional support and information for victims of
crime
Nottingham University Counselling Service: 0115 951 3695 Confidential counselling service.
Nightline: 0115 951 4985
Confidential listening and information service.
If you would like any more information regarding this study or if you wish to have an executive
summary of the study’s findings in June 2014, please feel free to contact me using the following
details:
Researcher: Divya Sukumar
Email: [email protected]
We would like to take this final opportunity to thank you again for your participation.
Student Beliefs about Police Interviews
45
Appendix 2: Participants’ Courses of Study
Course
Frequency Percent Valid Percent Cumulative Percent
Valid Architecture 1 1.4 1.4 1.4
Biology 1 1.4 1.4 2.9
Business Management 1 1.4 1.4 4.3
Economics 3 4.3 4.3 8.6
English 3 4.3 4.3 12.9
Environmental Engineering 3 4.3 4.3 17.1
Industrial Economics 1 1.4 1.4 18.6
Law 1 1.4 1.4 20.0
Medicine 1 1.4 1.4 21.4
Natural Sciences 1 1.4 1.4 22.9
Pharmacy 1 1.4 1.4 24.3
Psychology 47 67.1 67.1 91.4
Psychology, Cog. Neuroscience 4 5.7 5.7 97.1
Russian Studies 1 1.4 1.4 98.6
Sustainable Building 1 1.4 1.4 100.0
Total 70 100.0 100.0
Appendix 3: Participants’ Source of Information
Source_of_Information
Frequency Percent Valid Percent Cumulative Percent
Valid Descriptions from dad 2 2.9 2.9 2.9
Detective stories 2 2.9 2.9 5.7
First-hand experience 4 5.7 5.7 11.4
Friends/Family 1 1.4 1.4 12.9
Media, studying Psychology 1 1.4 1.4 14.3
Scripts of Interviews in Literature 1 1.4 1.4 15.7
Studying Law, TV 1 1.4 1.4 17.1
Studying Psychology 7 10.0 10.0 27.1
TV 30 42.9 42.9 70.0
TV, detective stories 14 20.0 20.0 90.0
TV, experience in Sri Lanka 1 1.4 1.4 91.4
TV, friends 1 1.4 1.4 92.9
TV, studying Psychology 4 5.7 5.7 98.6
Working with Victim Support, studying
Psychology 1 1.4 1.4 100.0
Total 70 100.0 100.0
Student Beliefs about Police Interviews
46
Appendix 4: Coding System
Code Event
ST Start of sequence
AA Suspect’s denial
AB Notice of caution2
AC Use polygraphs/physiological measures
AD Touch suspect in a friendly manner
AE Ask unexpected questions
AF Stare at suspect in silence
AG Reveal evidence to suspect
AH Repeat question over and over again
AI Show photos from witnesses
AJ Instil hopelessness in suspect
AK Insult suspect
AL Directly accuse suspect
AM Use deception
AN Accuse suspect of being someone else
AO Offer rewards for co-operation
AP Identify and meet basic needs
AQ Bluff suspect about having evidence
AR Find common ground
AS Morally rationalize alleged crime
AT Employ another interrogator (good cop/bad cop)
AU Threaten suspect
AV Flatter suspect
AW Suspect provides information about previous offences or co-suspects
AX Present self as someone other than the interrogator
AY Confront suspect without insulting
AZ Reduce fear
BA Misconstrue suspect’s words
BB Make angry/frustrated/impatient gestures
BC Suspect’s confession to full crime
BD Identify contradictions in suspect’s story
BE Suspect’s admission to part of the crime
BF Identify and exaggerate fears
BG Move interrogation from a neutral to formal setting
BH Dismiss suspect’s evidence
BI Confront suspect with fabricated evidence
BJ Move interrogation from a formal to neutral setting
BK Ask a series of questions without allowing suspect to answer
EN End of sequence
2 “You do not have to say anything. But it may harm your defence if you do not mention when questioned something which you later rely on in court. Anything you do say may be given in evidence.”
Student Beliefs about Police Interviews
47
Appendix 5: Data Strings for High Familiarity Condition
*003/ AP AB AG AZ AH AA AI AO AW BE BC
*005/ AB AP AG AF AA AY AG AT BE BD AI AO BC
*010/ AC AY AO AI AG AO BD BC
*014/ AB AF AO AY BK AS AR AC AE AH AI AW BD BE BG BH AD
*022/ AZ BK BF AP AR AI AB AD AM
*024/ AE AA AH AP AY AW AI AC BJ AT
*028/ AA AP AR AW AY AE AH AM AT BA BB AF AO BE BC
*029/ AA AE AF AH AK AU BA BK BE BD BE AI
*031/ AA AE AC
*035/ BG AB AF AE AL AA AH AA AH AA AT AG AI AO AW BH BD AL AY BA BE BC
*036/ AG AI AP AR AA AC AW AY BE BD BC
*037/ AB AA AF AO AP AR AZ AE AH AG AM AY BA BB AT BK BE AQ AS AJ AK BC
*039/ AB BG AY AW AG AO AI AS
*040/ AE AG AM AA BD AU AO AW AA AY
*047/ AB BG AP AR AX AY BK AH AZ AI AL AA BD
*050/ AB AP AW AY AE AM AG
*052/ AF AP AE AA AL AG AH AI AT AO AM
*053/ AP AT AB AA AY BD BH AG AI AE BC
*055/ AP AF AL AA AE AR AO BE BD BB AH BA AW
*056/ AF AE AA AG AH AR AX AY AW BD BE BG
*059/ AA AG AA AI AL BD BE BH AO BC
*062/ AB AA AP AW AF AE AH AI AM AN AO AQ AR BE BD BC
*064/ AP AY BA AE AF AG AH AM AR
*067/ AB AF AY AH AA AC AO AT AU AZ BI
*068/ AR AO AB AY AG BD AI
*070/ AB AI BB AH AA AC AO AP AZ BI BC
Appendix 6: Data Strings for Low Familiarity Condition
*001/ BE AC AF AB AL AA AH AI BF AM AE AQ AW BH BD BB BC
*002/ AP AB AA BJ AL AY AZ AC AM AH BD BE
*004/ AB AP AA AZ AE AI AO AW
*006/ AX AP AF AG AI AB AA AR AV AU BA BJ BH BK AJ AH AE AL AW BE BC AZ AP AO
*007/ AB AI AE AH AM BA AL AO AJ BE
*008/ AB AA AH AF AP AO AR AQ AY BD AL AJ BE BC
*009/ AB AY AG AO AH
*011/ BJ AG AE AH AF AQ AT AX
*012/ AX AY AB AA AO AQ AG AW BD AE BE
*013/ BJ AZ AA AB AR AP AG AI BD AY BE
*015/ AL AA AB BG AG AY AZ AW
*016/ AG AA AI AF AE AC AH AT BD BC
*017/ AJ AA AI AA AF AG AQ AH AO AW BE BC
*018/ AZ AE AG AO AR AT AY BC
*019/ AA AG AI BD BF AS Al AO AA AU BE AU BE
*020/ AO AX AS AI BH
Student Beliefs about Police Interviews
48
*021/ AC AP AB AE AA AH AI AG BC
*023/ AB AA AH BI BK BH
*025/ AB AP BG AE AH BD AO
*026/ AB AP AE AR AW AY AF BD
*027/ AE AP AW AY BD AA AH AM AR BB BE BC AB
*030/ AB AA AW AF AI AY BD AG BC AP
*032/ AE AA AF AH AA AY AG AO BD BH
*033/ AA AE AD BB AC AK AM
*034/ AD AI AG AA AE BF AH AZ AP AO BE BK AU BE
*038/ AF AG AI AV AE AT BF
*041/ AP AB AA AR AE BD BE AE BD AG BC
*042/ AB AF AY AS AO AA AG AI AA BA BB BD BG BF BK AU AE AA AG AH AQ
*043/ AE AA AF AT AG AH AM AN AQ AU BA BD BH BE BF BK BB AP AO AL AI AK AJ
*044/ AE AF BD AT AO AA AH AM AQ AU BE BI
*045/ AB AA AI BK AF AO AH BA BD BC
*046/ AB AF AA AE AH AI AK AJ AO AR AS AZ AV AL AT AQ AM BK BA AU AY BD BE BH BC
*048/ AB AF AO AG AY AH AI AL AJ BG BJ BK BE BD BC AZ AC AM AP AS AU AW AQ AR AT
*049/ AO AF AR AQ AE AH BK BA BD AG AI AM AL BE
*051/ AA AG AI AM AO AE AR AV AZ BD BE AE AH BE AZ AE BC
*054/ BG AP AX AL AE AJ AS BD AA AG AO AT BC
*057/ AB AP AR AZ AG AH AF AA AE BG AT AW BC
*058/ AY AA AW AF AA AH AG BD BE BC
*060/ BG AY AB AE AG AI AH AA AL AO BC
*061/ AB AP AE AH AF AC
*063/ AG AA AE AH AI AU BD
*065/ AB AP AR AA AY AA BD AA BE
*066/ AA BB AH AF BI AT BF AO
*069/ BG AP AL AY AW BD BH BK AC
Student Beliefs about Police Interviews
49
Appendix 7: Transitional Frequency Matrix for All Data
ST AA AB AE AF AG AH AI AO AP AR AW AY BC BD BE MF LF EN
ST 0 8 24 6 3 3 0 0 2 6 1 0 1 0 0 1 9 6 0
AA 0 0 2 8 4 7 10 5 1 2 2 2 5 0 3 1 9 2 0
AB 0 11 0 2 6 1 0 2 0 8 1 0 2 0 0 0 4 1 1
AE 0 7 0 0 3 3 12 1 0 1 3 0 0 2 2 1 8 3 0
AF 0 4 1 4 0 4 2 1 5 2 1 0 2 0 2 0 4 1 0
AG 0 4 0 1 1 0 6 11 6 0 0 1 2 3 2 0 5 0 1
AH 0 7 0 1 5 2 0 8 1 1 1 0 0 0 2 1 13 2 1
AI 0 2 2 2 1 3 1 0 4 1 0 1 1 0 2 0 11 6 2
AO 0 3 1 1 1 1 2 2 0 2 3 5 1 3 2 3 6 2 3
AP 0 1 4 3 2 2 0 0 4 0 7 3 2 0 0 0 4 2 1
AR 0 2 0 1 0 0 0 1 2 1 0 2 0 0 0 1 7 6 1
AW 0 1 0 0 3 1 0 1 0 0 0 0 5 1 4 3 3 0 3
AY 0 2 2 2 1 4 2 0 1 0 0 4 0 1 5 2 7 1 1
BC 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 25
BD 0 3 0 1 0 3 0 2 1 0 0 0 1 6 0 9 9 3 3
BE 0 0 0 2 0 0 0 1 0 0 0 0 0 8 6 0 9 2 8
MF 0 7 2 11 2 8 5 2 10 7 4 7 10 2 9 11 36 24 13
LF 0 1 0 1 1 1 5 2 4 3 1 0 3 3 2 3 24 8 7
EN 69 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Appendix 8: SPSS Output for Clustered Data
Antecedent * Sequitor Crosstabulation
Sequitor Total
AB EN FP LF MF RC ST
Anteceden
t
AB Count 0 1 25 1 4 8 0 39
Expected
Count 1.6 2.9 5.4 2.8 7.0 16.6 2.8 39.0
Std. Residual -1.3 -1.1 8.5 -1.1 -1.1 -2.1 -1.7
EN Count 0 0 0 0 0 0 69 69
Expected
Count 2.8 5.1 9.5 5.0 12.3 29.3 5.0 69.0
Std. Residual -1.7 -2.3 -3.1 -2.2 -3.5 -5.4 28.6
FP Count 7 1 15 5 17 86 0 131
Expected
Count 5.4 9.6 18.0 9.5 23.4 55.6 9.5 131.0
Std. Residual .7 -2.8 -.7 -1.5 -1.3 4.1 -3.1
LF Count 0 7 5 8 24 25 0 69
Student Beliefs about Police Interviews
50
Expected
Count 2.8 5.1 9.5 5.0 12.3 29.3 5.0 69.0
Std. Residual -1.7 .9 -1.5 1.3 3.3 -.8 -2.2
MF Count 2 13 16 24 36 79 0 170
Expected
Count 7.0 12.5 23.4 12.3 30.4 72.1 12.3 170.0
Std. Residual -1.9 .1 -1.5 3.3 1.0 .8 -3.5
RC Count 6 48 53 25 80 192 0 404
Expected
Count 16.6 29.7 55.6 29.3 72.1 171.4 29.3 404.0
Std. Residual -2.6 3.4 -.3 -.8 .9 1.6 -5.4
ST Count 24 0 17 6 9 14 0 70
Expected
Count 2.9 5.1 9.6 5.1 12.5 29.7 5.1 70.0
Std. Residual 12.5 -2.3 2.4 .4 -1.0 -2.9 -2.3
Total Count 39 70 131 69 170 404 69 952
Expected
Count 39.0 70.0 131.0 69.0 170.0 404.0 69.0 952.0
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 1293.617a 36 .000
Likelihood Ratio 719.791 36 .000
N of Valid Cases 952
a. 7 cells (14.3%) have expected count less than 5. The minimum expected count is 1.60.
Student Beliefs about Police Interviews
51
Appendix 9: SPSS Output
All Data
Antecedent * Sequitor Crosstabulation
Sequitor Total
AA AB AE AF AG AH AI AO AP AR AW AY BC BD BE EN LF MF ST
Antecedent
AA Count 0 2 8 4 7 10 5 1 2 2 2 5 0 3 1 0 2 9 0 63
Expected Count
4.2 2.6 3.0 2.2 2.8 3.0 2.6 2.7 2.3 1.6 1.7 2.3 1.9 2.7 2.4 4.6 4.6 11.3 4.6 63.0
% within Antecedent
0.0%
3.2%
12.7%
6.3%
11.1%
15.9%
7.9%
1.6%
3.2%
3.2%
3.2%
7.9%
0.0%
4.8%
1.6%
0.0%
3.2%
14.3%
0.0%
100.0%
Std. Residual
-2.0 -.4 2.8 1.2 2.5 4.1 1.5 -1.0 -.2 .3 .3 1.8 -1.4 .2 -.9 -2.2 -1.2 -.7 -
2.1
AB Count 11 0 2 6 1 0 2 0 8 1 0 2 0 0 0 1 1 4 0 39
Expected Count
2.6 1.6 1.9 1.4 1.8 1.8 1.6 1.7 1.4 1.0 1.0 1.4 1.2 1.7 1.5 2.9 2.8 7.0 2.8 39.0
% within Antecedent
28.2%
0.0%
5.1%
15.4%
2.6%
0.0%
5.1%
0.0%
20.5%
2.6%
0.0%
5.1%
0.0%
0.0%
0.0%
2.6%
2.6%
10.3%
0.0%
100.0%
Std. Residual
5.2 -1.3 .1 4.0 -.6 -1.4 .3 -1.3 5.5 .0 -1.0 .5 -1.1 -1.3 -1.2 -1.1 -1.1 -1.1 -
1.7
AE Count 7 0 0 3 3 12 1 0 1 3 0 0 2 2 1 0 3 8 0 46
Expected Count
3.0 1.9 2.2 1.6 2.1 2.2 1.9 2.0 1.7 1.2 1.2 1.7 1.4 2.0 1.7 3.4 3.3 8.2 3.3 46.0
% within Antecedent
15.2%
0.0%
0.0%
6.5%
6.5%
26.1%
2.2%
0.0%
2.2%
6.5%
0.0%
0.0%
4.3%
4.3%
2.2%
0.0%
6.5%
17.4%
0.0%
100.0%
Std. Residual
2.3 -1.4 -1.5 1.1 .6 6.7 -.6 -1.4 -.5 1.7 -1.1 -1.3 .5 .0 -.6 -1.8 -.2 -.1 -
1.8
AF Count 4 1 4 0 4 2 1 5 2 1 0 2 0 2 0 0 1 4 0 33
Expected Count
2.2 1.4 1.6 1.1 1.5 1.6 1.4 1.4 1.2 .8 .9 1.2 1.0 1.4 1.2 2.4 2.4 5.9 2.4 33.0
% within Antecedent
12.1%
3.0%
12.1%
0.0%
12.1%
6.1%
3.0%
15.2%
6.1%
3.0%
0.0%
6.1%
0.0%
6.1%
0.0%
0.0%
3.0%
12.1%
0.0%
100.0%
Std. Residual
1.2 -.3 1.9 -1.1 2.1 .4 -.3 3.0 .7 .2 -.9 .7 -1.0 .5 -1.1 -1.6 -.9 -.8 -
1.5
AG
Count 4 0 1 1 0 6 11 6 0 0 1 2 3 2 0 1 0 5 0 43
Expected Count
2.8 1.8 2.1 1.5 1.9 2.0 1.8 1.9 1.6 1.1 1.1 1.6 1.3 1.9 1.6 3.2 3.1 7.7 3.1 43.0
% within Antecedent
9.3%
0.0%
2.3%
2.3%
0.0%
14.0%
25.6%
14.0%
0.0%
0.0%
2.3%
4.7%
7.0%
4.7%
0.0%
2.3%
0.0%
11.6%
0.0%
100.0%
Std. Residual
.7 -1.3 -.7 -.4 -1.4 2.8 7.0 3.0 -1.3 -1.0 -.1 .3 1.5 .1 -1.3 -1.2 -1.8 -1.0 -
1.8
AH Count 7 0 1 5 2 0 8 1 1 1 0 0 0 2 1 1 2 13 0 45
Expected Count
3.0 1.8 2.2 1.6 2.0 2.1 1.8 1.9 1.7 1.1 1.2 1.7 1.4 1.9 1.7 3.3 3.3 8.0 3.3 45.0
% within Antecedent
15.6%
0.0%
2.2%
11.1%
4.4%
0.0%
17.8%
2.2%
2.2%
2.2%
0.0%
0.0%
0.0%
4.4%
2.2%
2.2%
4.4%
28.9%
0.0%
100.0%
Std. Residual
2.3 -1.4 -.8 2.8 .0 -1.5 4.5 -.7 -.5 -.1 -1.1 -1.3 -1.2 .0 -.5 -1.3 -.7 1.8 -
1.8
AI Count 2 2 2 1 3 1 0 4 1 0 1 1 0 2 0 2 6 11 0 39
Expected Count
2.6 1.6 1.9 1.4 1.8 1.8 1.6 1.7 1.4 1.0 1.0 1.4 1.2 1.7 1.5 2.9 2.8 7.0 2.8 39.0
% within Antecedent
5.1%
5.1%
5.1%
2.6%
7.7%
2.6%
0.0%
10.3%
2.6%
0.0%
2.6%
2.6%
0.0%
5.1%
0.0%
5.1%
15.4%
28.2%
0.0%
100.0%
Std. Residual
-.4 .3 .1 -.3 .9 -.6 -1.3 1.8 -.4 -1.0 .0 -.4 -1.1 .2 -1.2 -.5 1.9 1.5 -
1.7
AO
Count 3 1 1 1 1 2 2 0 2 3 5 1 3 2 3 3 2 6 0 41
Expected Count
2.7 1.7 2.0 1.4 1.9 1.9 1.7 1.8 1.5 1.0 1.1 1.5 1.2 1.8 1.6 3.0 3.0 7.3 3.0 41.0
% within Antecedent
7.3%
2.4%
2.4%
2.4%
2.4%
4.9%
4.9%
0.0%
4.9%
7.3%
12.2%
2.4%
7.3%
4.9%
7.3%
7.3%
4.9%
14.6%
0.0%
100.0%
Std. Residual
.2 -.5 -.7 -.4 -.6 .0 .2 -1.3 .4 1.9 3.8 -.4 1.6 .2 1.2 .0 -.6 -.5 -
1.7
AP Count 1 4 3 2 2 0 0 4 0 7 3 2 0 0 0 1 2 4 0 35
Expected Count
2.3 1.4 1.7 1.2 1.6 1.7 1.4 1.5 1.3 .9 .9 1.3 1.1 1.5 1.3 2.6 2.5 6.3 2.5 35.0
% within Antecedent
2.9%
11.4%
8.6%
5.7%
5.7%
0.0%
0.0%
11.4%
0.0%
20.0%
8.6%
5.7%
0.0%
0.0%
0.0%
2.9%
5.7%
11.4%
0.0%
100.0%
Std. Residual
-.9 2.1 1.0 .7 .3 -1.3 -1.2 2.0 -1.1 6.5 2.2 .6 -1.0 -1.2 -1.2 -1.0 -.3 -.9 -
1.6
AR Count 2 0 1 0 0 0 1 2 1 0 2 0 0 0 1 1 6 7 0 24
Expected Count
1.6 1.0 1.2 .8 1.1 1.1 1.0 1.0 .9 .6 .6 .9 .7 1.0 .9 1.8 1.7 4.3 1.7 24.0
% within Antecedent
8.3%
0.0%
4.2%
0.0%
0.0%
0.0%
4.2%
8.3%
4.2%
0.0%
8.3%
0.0%
0.0%
0.0%
4.2%
4.2%
25.0%
29.2%
0.0%
100.0%
Std. Residual
.3 -1.0 -.1 -.9 -1.0 -1.1 .0 1.0 .1 -.8 1.7 -.9 -.9 -1.0 .1 -.6 3.2 1.3 -
1.3
A Count 1 0 0 3 1 0 1 0 0 0 0 5 1 4 3 3 0 3 0 25
Student Beliefs about Police Interviews
52
W Expected Count
1.7 1.0 1.2 .9 1.1 1.2 1.0 1.1 .9 .6 .7 .9 .8 1.1 .9 1.8 1.8 4.5 1.8 25.0
% within Antecedent
4.0%
0.0%
0.0%
12.0%
4.0%
0.0%
4.0%
0.0%
0.0%
0.0%
0.0%
20.0%
4.0%
16.0%
12.0%
12.0%
0.0%
12.0%
0.0%
100.0%
Std. Residual
-.5 -1.0 -1.1 2.3 -.1 -1.1 .0 -1.0 -1.0 -.8 -.8 4.3 .3 2.8 2.1 .9 -1.3 -.7 -
1.3
AY Count 2 2 2 1 4 2 0 1 0 0 4 0 1 5 2 1 1 7 0 35
Expected Count
2.3 1.4 1.7 1.2 1.6 1.7 1.4 1.5 1.3 .9 .9 1.3 1.1 1.5 1.3 2.6 2.5 6.3 2.5 35.0
% within Antecedent
5.7%
5.7%
5.7%
2.9%
11.4%
5.7%
0.0%
2.9%
0.0%
0.0%
11.4%
0.0%
2.9%
14.3%
5.7%
2.9%
2.9%
20.0%
0.0%
100.0%
Std. Residual
-.2 .5 .2 -.2 1.9 .3 -1.2 -.4 -1.1 -.9 3.2 -1.1 -.1 2.8 .6 -1.0 -1.0 .3 -
1.6
BC Count 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 25 0 2 0 29
Expected Count
1.9 1.2 1.4 1.0 1.3 1.4 1.2 1.2 1.1 .7 .8 1.1 .9 1.2 1.1 2.1 2.1 5.2 2.1 29.0
% within Antecedent
0.0%
3.4%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
3.4%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
86.2%
0.0%
6.9%
0.0%
100.0%
Std. Residual
-1.4 -.2 -1.2 -1.0 -1.1 -1.2 -1.1 -1.1 -.1 -.9 -.9 -1.0 -.9 -1.1 -1.0 15.7 -1.4 -1.4 -
1.4
BD Count 3 0 1 0 3 0 2 1 0 0 0 1 6 0 9 3 3 9 0 41
Expected Count
2.7 1.7 2.0 1.4 1.9 1.9 1.7 1.8 1.5 1.0 1.1 1.5 1.2 1.8 1.6 3.0 3.0 7.3 3.0 41.0
% within Antecedent
7.3%
0.0%
2.4%
0.0%
7.3%
0.0%
4.9%
2.4%
0.0%
0.0%
0.0%
2.4%
14.6%
0.0%
22.0%
7.3%
7.3%
22.0%
0.0%
100.0%
Std. Residual
.2 -1.3 -.7 -1.2 .8 -1.4 .2 -.6 -1.2 -1.0 -1.0 -.4 4.3 -1.3 6.0 .0 .0 .6 -
1.7
BE Count 0 0 2 0 0 0 1 0 0 0 0 0 8 6 0 8 2 9 0 36
Expected Count
2.4 1.5 1.7 1.2 1.6 1.7 1.5 1.6 1.3 .9 .9 1.3 1.1 1.6 1.4 2.6 2.6 6.4 2.6 36.0
% within Antecedent
0.0%
0.0%
5.6%
0.0%
0.0%
0.0%
2.8%
0.0%
0.0%
0.0%
0.0%
0.0%
22.2%
16.7%
0.0%
22.2%
5.6%
25.0%
0.0%
100.0%
Std. Residual
-1.5 -1.2 .2 -1.1 -1.3 -1.3 -.4 -1.2 -1.2 -1.0 -1.0 -1.2 6.6 3.6 -1.2 3.3 -.4 1.0 -
1.6
EN Count 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 69 69
Expected Count
4.6 2.8 3.3 2.4 3.1 3.3 2.8 3.0 2.5 1.7 1.8 2.5 2.1 3.0 2.6 5.1 5.0 12.3 5.0 69.0
% within Antecedent
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
100.0%
100.0%
Std. Residual
-2.1 -1.7 -1.8 -1.5 -1.8 -1.8 -1.7 -1.7 -1.6 -1.3 -1.3 -1.6 -1.4 -1.7 -1.6 -2.3 -2.2 -3.5 28.
6
LF Count 1 0 1 1 1 5 2 4 3 1 0 3 3 2 3 7 8 24 0 69
Expected Count
4.6 2.8 3.3 2.4 3.1 3.3 2.8 3.0 2.5 1.7 1.8 2.5 2.1 3.0 2.6 5.1 5.0 12.3 5.0 69.0
% within Antecedent
1.4%
0.0%
1.4%
1.4%
1.4%
7.2%
2.9%
5.8%
4.3%
1.4%
0.0%
4.3%
4.3%
2.9%
4.3%
10.1%
11.6%
34.8%
0.0%
100.0%
Std. Residual
-1.7 -1.7 -1.3 -.9 -1.2 1.0 -.5 .6 .3 -.6 -1.3 .3 .6 -.6 .2 .9 1.3 3.3 -
2.2
MF
Count 7 2 11 2 8 5 2 10 7 4 7 10 2 9 11 13 24 36 0 170
Expected Count
11.3 7.0 8.2 5.9 7.7 8.0 7.0 7.3 6.3 4.3 4.5 6.3 5.2 7.3 6.4 12.5 12.3 30.4 12.
3 170.0
% within Antecedent
4.1%
1.2%
6.5%
1.2%
4.7%
2.9%
1.2%
5.9%
4.1%
2.4%
4.1%
5.9%
1.2%
5.3%
6.5%
7.6%
14.1%
21.2%
0.0%
100.0%
Std. Residual
-1.3 -1.9 1.0 -1.6 .1 -1.1 -1.9 1.0 .3 -.1 1.2 1.5 -1.4 .6 1.8 .1 3.3 1.0 -
3.5
ST Count 8 24 6 3 3 0 0 2 6 1 0 1 0 0 1 0 6 9 0 70
Expected Count
4.6 2.9 3.4 2.4 3.2 3.3 2.9 3.0 2.6 1.8 1.8 2.6 2.1 3.0 2.6 5.1 5.1 12.5 5.1 70.0
% within Antecedent
11.4%
34.3%
8.6%
4.3%
4.3%
0.0%
0.0%
2.9%
8.6%
1.4%
0.0%
1.4%
0.0%
0.0%
1.4%
0.0%
8.6%
12.9%
0.0%
100.0%
Std. Residual
1.6 12.5 1.4 .4 -.1 -1.8 -1.7 -.6 2.1 -.6 -1.4 -1.0 -1.5 -1.7 -1.0 -2.3 .4 -1.0 -
2.3
Total Count 63 39 46 33 43 45 39 41 35 24 25 35 29 41 36 70 69 170 69 952
Expected Count
63.0 39.0 46.0 33.0 43.0 45.0 39.0 41.0 35.0 24.0 25.0 35.0 29.0 41.0 36.0 70.0 69.0 170.
0 69.
0 952.0
% within Antecedent
6.6%
4.1%
4.8%
3.5%
4.5%
4.7%
4.1%
4.3%
3.7%
2.5%
2.6%
3.7%
3.0%
4.3%
3.8%
7.4%
7.2%
17.9%
7.2%
100.0%
Chi-Square Tests
Value df Asymp. Sig. (2-
sided)
Pearson Chi-Square
2191.390a 324 .000
Likelihood Ratio
1375.813 324 .000
N of Valid Cases
952
a. 319 cells (88.4%) have expected count less than 5. The minimum expected count is .61.
Student Beliefs about Police Interviews
53
High Familiarity
Antecedent * Sequitor Crosstabulation
Sequitor Total
AA AB AE AF AG AH AI AO AP AR AW AY BC BD BE EN LF MF ST
Antecedent
AA Count 0 0 3 1 2 3 2 0 2 0 0 3 0 2 0 0 0 5 0 23
Expected Count
1.5 .9 1.0 .8 1.0 1.0 1.1 1.1 1.0 .7 .8 1.1 .7 .9 .8 1.7 1.2 3.9 1.6 23.0
% within Antecedent
0.0%
0.0%
13.0%
4.3%
8.7%
13.0%
8.7%
0.0%
8.7%
0.0%
0.0%
13.0%
0.0%
8.7%
0.0%
0.0%
0.0%
21.7%
0.0% 100.0%
Std. Residual
-1.2 -1.0 2.0 .2 .9 1.9 .8 -1.1 1.0 -.8 -.9 1.8 -.8 1.1 -.9 -1.3 -1.1 .6 -1.3
AB Count 3 0 0 3 1 0 1 0 2 0 0 1 0 0 0 0 1 2 0 14
Expected Count
.9 .6 .6 .5 .6 .6 .7 .7 .6 .4 .5 .7 .4 .6 .5 1.0 .8 2.4 1.0 14.0
% within Antecedent
21.4%
0.0%
0.0%
21.4%
7.1%
0.0%
7.1%
0.0%
14.3%
0.0%
0.0%
7.1%
0.0%
0.0%
0.0%
0.0%
7.1%
14.3%
0.0% 100.0%
Std. Residual
2.2 -.7 -.8 3.7 .5 -.8 .4 -.8 1.8 -.7 -.7 .4 -.7 -.7 -.7 -1.0 .3 -.2 -1.0
AE Count 3 0 0 2 1 4 0 0 0 1 0 0 1 0 0 0 0 3 0 15
Expected Count
1.0 .6 .6 .5 .7 .7 .7 .7 .6 .5 .5 .7 .5 .6 .6 1.1 .8 2.5 1.1 15.0
% within Antecedent
20.0%
0.0%
0.0%
13.3%
6.7%
26.7%
0.0%
0.0%
0.0%
6.7%
0.0%
0.0%
6.7%
0.0%
0.0%
0.0%
0.0%
20.0%
0.0% 100.0%
Std. Residual
2.0 -.8 -.8 2.1 .4 4.0 -.8 -.8 -.8 .8 -.7 -.8 .8 -.8 -.7 -1.1 -.9 .3 -1.0
AF Count 1 0 3 0 1 1 0 3 1 0 0 1 0 0 0 0 0 1 0 12
Expected Count
.8 .5 .5 .4 .5 .5 .6 .6 .5 .4 .4 .6 .4 .5 .4 .9 .6 2.0 .8 12.0
% within Antecedent
8.3%
0.0%
25.0%
0.0%
8.3%
8.3%
0.0%
25.0%
8.3%
0.0%
0.0%
8.3%
0.0%
0.0%
0.0%
0.0%
0.0%
8.3%
0.0% 100.0%
Std. Residual
.2 -.7 3.5 -.6 .6 .6 -.8 3.2 .7 -.6 -.6 .6 -.6 -.7 -.7 -.9 -.8 -.7 -.9
AG
Count 1 0 0 1 0 3 3 2 0 0 0 0 0 1 0 1 0 4 0 16
Expected Count
1.0 .6 .7 .5 .7 .7 .8 .8 .7 .5 .5 .8 .5 .6 .6 1.2 .9 2.7 1.1 16.0
% within Antecedent
6.3%
0.0%
0.0%
6.3%
0.0%
18.8%
18.8%
12.5%
0.0%
0.0%
0.0%
0.0%
0.0%
6.3%
0.0%
6.3%
0.0%
25.0%
0.0% 100.0%
Std. Residual
.0 -.8 -.8 .6 -.9 2.7 2.5 1.4 -.8 -.7 -.7 -.9 -.7 .5 -.8 -.2 -.9 .8 -1.1
AH Count 5 0 0 0 1 0 3 0 1 1 0 0 0 0 0 0 1 4 0 16
Expected Count
1.0 .6 .7 .5 .7 .7 .8 .8 .7 .5 .5 .8 .5 .6 .6 1.2 .9 2.7 1.1 16.0
% within Antecedent
31.3%
0.0%
0.0%
0.0%
6.3%
0.0%
18.8%
0.0%
6.3%
6.3%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
6.3%
25.0%
0.0% 100.0%
Std. Residual
3.9 -.8 -.8 -.7 .3 -.9 2.5 -.9 .4 .7 -.7 -.9 -.7 -.8 -.8 -1.1 .1 .8 -1.1
AI Count 0 1 1 0 1 0 0 3 1 0 1 0 0 0 0 2 2 5 0 17
Expected Count
1.1 .7 .7 .6 .8 .8 .8 .8 .7 .5 .6 .8 .5 .7 .6 1.3 .9 2.9 1.2 17.0
% within Antecedent
0.0%
5.9%
5.9%
0.0%
5.9%
0.0%
0.0%
17.6%
5.9%
0.0%
5.9%
0.0%
0.0%
0.0%
0.0%
11.8%
11.8%
29.4%
0.0% 100.0%
Std. Residual
-1.1 .4 .3 -.8 .3 -.9 -.9 2.4 .3 -.7 .6 -.9 -.7 -.8 -.8 .7 1.1 1.2 -1.1
AO
Count 0 1 0 0 0 0 2 0 2 0 3 1 2 1 2 0 0 3 0 17
Expected Count
1.1 .7 .7 .6 .8 .8 .8 .8 .7 .5 .6 .8 .5 .7 .6 1.3 .9 2.9 1.2 17.0
% within Antecedent
0.0%
5.9%
0.0%
0.0%
0.0%
0.0%
11.8%
0.0%
11.8%
0.0%
17.6%
5.9%
11.8%
5.9%
11.8%
0.0%
0.0%
17.6%
0.0% 100.0%
Std. Residual
-1.1 .4 -.8 -.8 -.9 -.9 1.3 -.9 1.5 -.7 3.2 .2 2.0 .4 1.7 -1.1 -1.0 .1 -1.1
AP Count 0 1 1 1 1 0 0 0 0 5 2 2 0 0 0 0 0 2 0 15
Expected Count
1.0 .6 .6 .5 .7 .7 .7 .7 .6 .5 .5 .7 .5 .6 .6 1.1 .8 2.5 1.1 15.0
% within Antecedent
0.0%
6.7%
6.7%
6.7%
6.7%
0.0%
0.0%
0.0%
0.0%
33.3%
13.3%
13.3%
0.0%
0.0%
0.0%
0.0%
0.0%
13.3%
0.0% 100.0%
Std. Residual
-1.0 .5 .5 .7 .4 -.8 -.8 -.8 -.8 6.6 2.1 1.5 -.7 -.8 -.7 -1.1 -.9 -.3 -1.0
AR Count 1 0 0 0 0 0 1 2 0 0 1 0 0 0 1 1 2 2 0 11
Expected Count
.7 .4 .5 .4 .5 .5 .5 .5 .5 .3 .4 .5 .3 .4 .4 .8 .6 1.9 .8 11.0
% within Antecedent
9.1%
0.0%
0.0%
0.0%
0.0%
0.0%
9.1%
18.2%
0.0%
0.0%
9.1%
0.0%
0.0%
0.0%
9.1%
9.1%
18.2%
18.2%
0.0% 100.0%
Std. Residual
.3 -.7 -.7 -.6 -.7 -.7 .6 2.0 -.7 -.6 1.0 -.7 -.6 -.7 .9 .2 1.8 .1 -.9
AW
Count 1 0 0 1 1 0 1 0 0 0 0 3 0 2 1 1 0 1 0 12
Expected Count
.8 .5 .5 .4 .5 .5 .6 .6 .5 .4 .4 .6 .4 .5 .4 .9 .6 2.0 .8 12.0
% within Antecedent
8.3%
0.0%
0.0%
8.3%
8.3%
0.0%
8.3%
0.0%
0.0%
0.0%
0.0%
25.0%
0.0%
16.7%
8.3%
8.3%
0.0%
8.3%
0.0% 100.0%
Std. Residual
.2 -.7 -.7 .9 .6 -.7 .6 -.8 -.7 -.6 -.6 3.2 -.6 2.2 .8 .1 -.8 -.7 -.9
AY Count 0 0 2 0 2 1 0 1 0 0 3 0 0 1 1 1 0 5 0 17
Student Beliefs about Police Interviews
54
Expected Count
1.1 .7 .7 .6 .8 .8 .8 .8 .7 .5 .6 .8 .5 .7 .6 1.3 .9 2.9 1.2 17.0
% within Antecedent
0.0%
0.0%
11.8%
0.0%
11.8%
5.9%
0.0%
5.9%
0.0%
0.0%
17.6%
0.0%
0.0%
5.9%
5.9%
5.9%
0.0%
29.4%
0.0% 100.0%
Std. Residual
-1.1 -.8 1.5 -.8 1.4 .3 -.9 .2 -.8 -.7 3.2 -.9 -.7 .4 .5 -.2 -1.0 1.2 -1.1
BC Count 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11
Expected Count
.7 .4 .5 .4 .5 .5 .5 .5 .5 .3 .4 .5 .3 .4 .4 .8 .6 1.9 .8 11.0
% within Antecedent
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
100.0%
0.0%
0.0%
0.0% 100.0%
Std. Residual
-.8 -.7 -.7 -.6 -.7 -.7 -.7 -.7 -.7 -.6 -.6 -.7 -.6 -.7 -.6 11.3 -.8 -1.4 -.9
BD Count 0 0 0 0 0 0 2 0 0 0 0 0 3 0 4 1 1 3 0 14
Expected Count
.9 .6 .6 .5 .6 .6 .7 .7 .6 .4 .5 .7 .4 .6 .5 1.0 .8 2.4 1.0 14.0
% within Antecedent
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
14.3%
0.0%
0.0%
0.0%
0.0%
0.0%
21.4%
0.0%
28.6%
7.1%
7.1%
21.4%
0.0% 100.0%
Std. Residual
-1.0 -.7 -.8 -.7 -.8 -.8 1.6 -.8 -.8 -.7 -.7 -.8 3.9 -.7 4.9 .0 .3 .4 -1.0
BE Count 0 0 0 0 0 0 1 0 0 0 0 0 3 5 0 0 0 4 0 13
Expected Count
.8 .5 .6 .4 .6 .6 .6 .6 .6 .4 .4 .6 .4 .5 .5 1.0 .7 2.2 .9 13.0
% within Antecedent
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
7.7%
0.0%
0.0%
0.0%
0.0%
0.0%
23.1%
38.5%
0.0%
0.0%
0.0%
30.8%
0.0% 100.0%
Std. Residual
-.9 -.7 -.7 -.7 -.8 -.8 .5 -.8 -.7 -.6 -.7 -.8 4.1 6.2 -.7 -1.0 -.8 1.2 -1.0
EN Count 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 25
Expected Count
1.6 1.0 1.1 .8 1.1 1.1 1.2 1.2 1.1 .8 .8 1.2 .8 1.0 .9 1.8 1.3 4.2 1.8 25.0
% within Antecedent
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
100.0%
100.0%
Std. Residual
-1.3 -1.0 -1.0 -.9 -1.1 -1.1 -1.1 -1.1 -1.0 -.9 -.9 -1.1 -.9 -1.0 -1.0 -1.4 -1.2 -2.1 17.5
LF Count 0 0 0 1 0 2 0 1 1 1 0 2 2 0 0 3 2 4 0 19
Expected Count
1.2 .8 .8 .6 .9 .9 .9 .9 .8 .6 .6 .9 .6 .8 .7 1.4 1.0 3.2 1.3 19.0
% within Antecedent
0.0%
0.0%
0.0%
5.3%
0.0%
10.5%
0.0%
5.3%
5.3%
5.3%
0.0%
10.5%
10.5%
0.0%
0.0%
15.8%
10.5%
21.1%
0.0% 100.0%
Std. Residual
-1.1 -.9 -.9 .4 -.9 1.2 -1.0 .1 .2 .5 -.8 1.1 1.8 -.9 -.8 1.4 1.0 .4 -1.2
MF
Count 4 2 3 0 4 2 1 5 1 2 2 4 0 2 4 5 10 9 0 60
Expected Count
3.9 2.4 2.5 2.0 2.7 2.7 2.9 2.9 2.5 1.9 2.0 2.9 1.9 2.4 2.2 4.4 3.2 10.2 4.2 60.0
% within Antecedent
6.7%
3.3%
5.0%
0.0%
6.7%
3.3%
1.7%
8.3%
1.7%
3.3%
3.3%
6.7%
0.0%
3.3%
6.7%
8.3%
16.7%
15.0%
0.0% 100.0%
Std. Residual
.0 -.2 .3 -1.4 .8 -.4 -1.1 1.2 -1.0 .1 .0 .7 -1.4 -.2 1.2 .3 3.8 -.4 -2.1
ST Count 4 9 2 2 1 0 0 0 4 1 0 0 0 0 0 0 0 3 0 26
Expected Count
1.7 1.0 1.1 .9 1.2 1.2 1.3 1.3 1.1 .8 .9 1.3 .8 1.0 1.0 1.9 1.4 4.4 1.8 26.0
% within Antecedent
15.4%
34.6%
7.7%
7.7%
3.8%
0.0%
0.0%
0.0%
15.4%
3.8%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
11.5%
0.0% 100.0%
Std. Residual
1.8 7.8 .9 1.2 -.2 -1.1 -1.1 -1.1 2.8 .2 -.9 -1.1 -.9 -1.0 -1.0 -1.4 -1.2 -.7 -1.4
Total Count 23 14 15 12 16 16 17 17 15 11 12 17 11 14 13 26 19 60 25 353
Expected Count
23.0 14.0 15.0 12.0 16.0 16.0 17.0 17.0 15.0 11.0 12.0 17.0 11.0 14.0 13.0 26.0 19.0 60.0 25.0 353.
0
% within Antecedent
6.5%
4.0%
4.2%
3.4%
4.5%
4.5%
4.8%
4.8%
4.2%
3.1%
3.4%
4.8%
3.1%
4.0%
3.7%
7.4%
5.4%
17.0%
7.1% 100.0%
Chi-Square Tests
Value df
Asymp. Sig.
(2-sided)
Pearson Chi-Square 1065.382a 324 .000
Likelihood Ratio 699.098 324 .000
N of Valid Cases 353
a. 360 cells (99.7%) have expected count less than 5. The
minimum expected count is .34.
Student Beliefs about Police Interviews
55
Low Familiarity
Antecedent * Sequitor
Crosstabulation
Sequitor Tota
l
AA AB AE AF AG AH AI AO AP AR AW AY BC BD BE EN LF MF ST
Antecedent
AA Count 0 2 5 3 5 7 3 1 0 2 2 2 0 1 1 0 2 4 0 40
Expected Count 2.7 1.7 2.1 1.4 1.8 1.9 1.5 1.6 1.3 .9 .9 1.2 1.2 1.8 1.5 2.9 3.3 7.4 2.9 40.0
% within Antecedent
0.0%
5.0%
12.5%
7.5%
12.5%
17.5%
7.5%
2.5%
0.0%
5.0%
5.0%
5.0%
0.0%
2.5%
2.5%
0.0%
5.0%
10.0%
0.0%
100.0%
Std. Residual -1.6 .3 2.0 1.3 2.4 3.6 1.3 -.5 -1.2 1.2 1.2 .7 -1.1 -.6 -.4 -1.7 -.7 -1.2 -1.7
AB Count 8 0 2 3 0 0 1 0 6 1 0 1 0 0 0 1 0 2 0 25
Expected Count 1.7 1.0 1.3 .9 1.1 1.2 .9 1.0 .8 .5 .5 .8 .8 1.1 1.0 1.8 2.1 4.6 1.8 25.0
% within Antecedent
32.0%
0.0%
8.0%
12.0%
0.0%
0.0%
4.0%
0.0%
24.0%
4.0%
0.0%
4.0%
0.0%
0.0%
0.0%
4.0%
0.0%
8.0%
0.0%
100.0%
Std. Residual 4.9 -1.0 .6 2.3 -1.1 -1.1 .1 -1.0 5.6 .6 -.7 .3 -.9 -1.1 -1.0 -.6 -1.4 -1.2 -1.3
AE Count 4 0 0 1 2 8 1 0 1 2 0 0 1 2 1 0 3 5 0 31
Expected Count 2.1 1.3 1.6 1.1 1.4 1.5 1.1 1.2 1.0 .7 .7 .9 .9 1.4 1.2 2.3 2.6 5.7 2.2 31.0
% within Antecedent
12.9%
0.0%
0.0%
3.2%
6.5%
25.8%
3.2%
0.0%
3.2%
6.5%
0.0%
0.0%
3.2%
6.5%
3.2%
0.0%
9.7%
16.1%
0.0%
100.0%
Std. Residual 1.3 -1.1 -1.3 -.1 .5 5.3 -.1 -1.1 .0 1.6 -.8 -1.0 .1 .5 -.2 -1.5 .3 -.3 -1.5
AF Count 3 1 1 0 3 1 1 2 1 1 0 1 0 2 0 0 1 3 0 21
Expected Count 1.4 .9 1.1 .7 .9 1.0 .8 .8 .7 .5 .5 .6 .6 .9 .8 1.5 1.8 3.9 1.5 21.0
% within Antecedent
14.3%
4.8%
4.8%
0.0%
14.3%
4.8%
4.8%
9.5%
4.8%
4.8%
0.0%
4.8%
0.0%
9.5%
0.0%
0.0%
4.8%
14.3%
0.0%
100.0%
Std. Residual 1.3 .1 -.1 -.9 2.1 .0 .3 1.3 .4 .8 -.7 .5 -.8 1.1 -.9 -1.2 -.6 -.4 -1.2
AG
Count 3 0 1 0 0 3 8 4 0 0 1 2 3 1 0 0 0 1 0 27
Expected Count 1.8 1.1 1.4 .9 1.2 1.3 1.0 1.1 .9 .6 .6 .8 .8 1.2 1.0 2.0 2.3 5.0 1.9 27.0
% within Antecedent
11.1%
0.0%
3.7%
0.0%
0.0%
11.1%
29.6%
14.8%
0.0%
0.0%
3.7%
7.4%
11.1%
3.7%
0.0%
0.0%
0.0%
3.7%
0.0%
100.0%
Std. Residual .9 -1.1 -.3 -1.0 -1.1 1.5 7.0 2.8 -1.0 -.8 .5 1.3 2.4 -.2 -1.0 -1.4 -1.5 -1.8 -1.4
AH Count 2 0 1 5 1 0 5 1 0 0 0 0 0 2 1 1 1 9 0 29
Expected Count 1.9 1.2 1.5 1.0 1.3 1.4 1.1 1.2 1.0 .6 .6 .9 .9 1.3 1.1 2.1 2.4 5.3 2.1 29.0
% within Antecedent
6.9%
0.0%
3.4%
17.2%
3.4%
0.0%
17.2%
3.4%
0.0%
0.0%
0.0%
0.0%
0.0%
6.9%
3.4%
3.4%
3.4%
31.0%
0.0%
100.0%
Std. Residual .0 -1.1 -.4 3.9 -.3 -1.2 3.8 -.2 -1.0 -.8 -.8 -.9 -.9 .6 -.1 -.8 -.9 1.6 -1.4
AI Count 2 1 1 1 2 1 0 1 0 0 0 1 0 2 0 0 4 6 0 22
Expected Count 1.5 .9 1.1 .8 1.0 1.1 .8 .9 .7 .5 .5 .7 .7 1.0 .8 1.6 1.8 4.0 1.6 22.0
% within Antecedent
9.1%
4.5%
4.5%
4.5%
9.1%
4.5%
0.0%
4.5%
0.0%
0.0%
0.0%
4.5%
0.0%
9.1%
0.0%
0.0%
18.2%
27.3%
0.0%
100.0%
Std. Residual .4 .1 -.1 .3 1.0 -.1 -.9 .1 -.9 -.7 -.7 .4 -.8 1.0 -.9 -1.3 1.6 1.0 -1.3
AO
Count 3 0 1 1 1 2 0 0 0 3 2 0 1 1 1 3 2 3 0 24
Expected Count 1.6 1.0 1.2 .8 1.1 1.2 .9 1.0 .8 .5 .5 .7 .7 1.1 .9 1.8 2.0 4.4 1.7 24.0
% within Antecedent
12.5%
0.0%
4.2%
4.2%
4.2%
8.3%
0.0%
0.0%
0.0%
12.5%
8.3%
0.0%
4.2%
4.2%
4.2%
12.5%
8.3%
12.5%
0.0%
100.0%
Std. Residual
1.1 -1.0 -.2 .2 -.1 .8 -.9 -1.0 -.9 3.4 2.0 -.8 .3 -.1 .1 .9 .0 -.7 -1.3
AP Count 1 3 2 1 1 0 0 4 0 2 1 0 0 0 0 1 2 2 0 20
Expected Count
1.3 .8 1.0 .7 .9 1.0 .7 .8 .7 .4 .4 .6 .6 .9 .8 1.5 1.7 3.7 1.4 20.0
% within Antecedent
5.0%
15.0%
10.0%
5.0%
5.0%
0.0%
0.0%
20.0%
0.0%
10.0%
5.0%
0.0%
0.0%
0.0%
0.0%
5.0%
10.0%
10.0%
0.0%
100.0%
Student Beliefs about Police Interviews
56
Std. Residual
-.3 2.4 .9 .4 .1 -1.0 -.9 3.6 -.8 2.4 .9 -.8 -.8 -1.0 -.9 -.4 .3 -.9 -1.2
AR Count 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 4 5 0 13
Expected Count
.9 .5 .7 .5 .6 .6 .5 .5 .4 .3 .3 .4 .4 .6 .5 1.0 1.1 2.4 .9 13.0
% within Antecedent
7.7%
0.0%
7.7%
0.0%
0.0%
0.0%
0.0%
0.0%
7.7%
0.0%
7.7%
0.0%
0.0%
0.0%
0.0%
0.0%
30.8%
38.5%
0.0%
100.0%
Std. Residual
.1 -.7 .4 -.7 -.8 -.8 -.7 -.7 .9 -.5 1.3 -.6 -.6 -.8 -.7 -1.0 2.8 1.7 -1.0
AW
Count 0 0 0 2 0 0 0 0 0 0 0 2 1 2 2 2 0 2 0 13
Expected Count
.9 .5 .7 .5 .6 .6 .5 .5 .4 .3 .3 .4 .4 .6 .5 1.0 1.1 2.4 .9 13.0
% within Antecedent
0.0%
0.0%
0.0%
15.4%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
15.4%
7.7%
15.4%
15.4%
15.4%
0.0%
15.4%
0.0%
100.0%
Std. Residual
-.9 -.7 -.8 2.3 -.8 -.8 -.7 -.7 -.7 -.5 -.5 2.6 1.0 1.8 2.1 1.1 -1.0 -.3 -1.0
AY Count 2 2 0 1 2 1 0 0 0 0 1 0 1 4 1 0 1 2 0 18
Expected Count
1.2 .8 .9 .6 .8 .9 .7 .7 .6 .4 .4 .5 .5 .8 .7 1.3 1.5 3.3 1.3 18.0
% within Antecedent
11.1%
11.1%
0.0%
5.6%
11.1%
5.6%
0.0%
0.0%
0.0%
0.0%
5.6%
0.0%
5.6%
22.2%
5.6%
0.0%
5.6%
11.1%
0.0%
100.0%
Std. Residual
.7 1.4 -1.0 .5 1.3 .1 -.8 -.8 -.8 -.6 1.0 -.7 .6 3.5 .4 -1.2 -.4 -.7 -1.1
BC Count 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 14 0 2 0 18
Expected Count
1.2 .8 .9 .6 .8 .9 .7 .7 .6 .4 .4 .5 .5 .8 .7 1.3 1.5 3.3 1.3 18.0
% within Antecedent
0.0%
5.6%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
5.6%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
77.8%
0.0%
11.1%
0.0%
100.0%
Std. Residual
-1.1 .3 -1.0 -.8 -.9 -.9 -.8 -.8 .5 -.6 -.6 -.7 -.7 -.9 -.8 11.0 -1.2 -.7 -1.1
BD Count 3 0 1 0 3 0 0 1 0 0 0 1 3 0 5 2 2 6 0 27
Expected Count
1.8 1.1 1.4 .9 1.2 1.3 1.0 1.1 .9 .6 .6 .8 .8 1.2 1.0 2.0 2.3 5.0 1.9 27.0
% within Antecedent
11.1%
0.0%
3.7%
0.0%
11.1%
0.0%
0.0%
3.7%
0.0%
0.0%
0.0%
3.7%
11.1%
0.0%
18.5%
7.4%
7.4%
22.2%
0.0%
100.0%
Std. Residual
.9 -1.1 -.3 -1.0 1.6 -1.1 -1.0 -.1 -1.0 -.8 -.8 .2 2.4 -1.1 3.9 .0 -.2 .5 -1.4
BE Count 0 0 2 0 0 0 0 0 0 0 0 0 5 1 0 8 2 5 0 23
Expected Count
1.5 1.0 1.2 .8 1.0 1.1 .8 .9 .8 .5 .5 .7 .7 1.0 .9 1.7 1.9 4.2 1.7 23.0
% within Antecedent
0.0%
0.0%
8.7%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
21.7%
4.3%
0.0%
34.8%
8.7%
21.7%
0.0%
100.0%
Std. Residual
-1.2 -1.0 .7 -.9 -1.0 -1.1 -.9 -1.0 -.9 -.7 -.7 -.8 5.2 .0 -.9 4.8 .1 .4 -1.3
EN Count 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 43 43
Expected Count
2.9 1.8 2.2 1.5 1.9 2.1 1.6 1.7 1.4 .9 .9 1.3 1.3 1.9 1.7 3.2 3.6 7.9 3.1 43.0
% within Antecedent
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
100.0%
100.0%
Std. Residual
-1.7 -1.3 -1.5 -1.2 -1.4 -1.4 -1.3 -1.3 -1.2 -1.0 -1.0 -1.1 -1.1 -1.4 -1.3 -1.8 -1.9 -2.8 22.7
LF Count 1 0 1 0 1 3 2 3 2 0 0 1 1 2 3 4 6 20 0 50
Expected Count
3.3 2.1 2.6 1.8 2.3 2.4 1.8 2.0 1.7 1.1 1.1 1.5 1.5 2.3 1.9 3.7 4.2 9.2 3.6 50.0
% within Antecedent
2.0%
0.0%
2.0%
0.0%
2.0%
6.0%
4.0%
6.0%
4.0%
0.0%
0.0%
2.0%
2.0%
4.0%
6.0%
8.0%
12.0%
40.0%
0.0%
100.0%
Std. Residual
-1.3 -1.4 -1.0 -1.3 -.8 .4 .1 .7 .3 -1.0 -1.0 -.4 -.4 -.2 .8 .2 .9 3.6 -1.9
MF
Count 3 0 8 2 4 3 1 5 6 2 5 6 2 7 7 8 14 27 0 110
Expected Count
7.4 4.6 5.7 3.9 5.0 5.3 4.0 4.4 3.7 2.4 2.4 3.3 3.3 5.0 4.2 8.1 9.2 20.2 7.9 110.
0
% within Antecedent
2.7%
0.0%
7.3%
1.8%
3.6%
2.7%
0.9%
4.5%
5.5%
1.8%
4.5%
5.5%
1.8%
6.4%
6.4%
7.3%
12.7%
24.5%
0.0%
100.0%
Std. Residual
-1.6 -2.1 1.0 -.9 -.4 -1.0 -1.5 .3 1.2 -.3 1.7 1.5 -.7 .9 1.3 .0 1.6 1.5 -2.8
ST Count 4 15 4 1 2 0 0 2 2 0 0 1 0 0 1 0 6 6 0 44
Expected Count
2.9 1.8 2.3 1.5 2.0 2.1 1.6 1.8 1.5 1.0 1.0 1.3 1.3 2.0 1.7 3.2 3.7 8.1 3.2 44.0
% within Antecedent
9.1%
34.1%
9.1%
2.3%
4.5%
0.0%
0.0%
4.5%
4.5%
0.0%
0.0%
2.3%
0.0%
0.0%
2.3%
0.0%
13.6%
13.6%
0.0%
100.0%
Std. Residual
.6 9.7 1.1 -.4 .0 -1.5 -1.3 .2 .4 -1.0 -1.0 -.3 -1.2 -1.4 -.5 -1.8 1.2 -.7 -1.8
Total Count 40 25 31 21 27 29 22 24 20 13 13 18 18 27 23 44 50 110 43 598
Expected Count 40.0 25.0 31.0 21.0 27.0 29.0 22.0 24.0 20.0 13.0 13.0 18.0 18.0 27.0 23.0 44.0 50.0
110.0
43.0 598.
0
% within Antecedent
6.7%
4.2%
5.2%
3.5%
4.5%
4.8%
3.7%
4.0%
3.3%
2.2%
2.2%
3.0%
3.0%
4.5%
3.8%
7.4%
8.4%
18.4%
7.2%
100.0%
Student Beliefs about Police Interviews
57
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 1417.307a 324 .000
Likelihood Ratio 928.515 324 .000
N of Valid Cases 598
a. 348 cells (96.4%) have expected count less than 5. The minimum expected count is
.28.
Appendix 10: Transitional Frequency Matrices for Dawkins Method
ST AA AB AE AF AG AH AI AO AP AR AW AY BC BD BE MF LF EN
ST 0 8 24 6 3 3 0 0 2 6 1 0 1 0 0 1 9 6 0
AA 0 0 2 8 4 7 10 5 1 2 2 2 5 0 3 1 9 2 0
AB 0 11 0 2 6 1 0 2 0 8 1 0 2 0 0 0 4 1 1
AE 0 7 0 0 3 3 12 1 0 1 3 0 0 2 2 1 8 3 0
AF 0 4 1 4 0 4 2 1 5 2 1 0 2 0 2 0 4 1 0
AG 0 4 0 1 1 0 6 11 6 0 0 1 2 3 2 0 5 0 1
AH 0 7 0 1 5 2 0 8 1 1 1 0 0 0 2 1 13 2 1
AI 0 2 2 2 1 3 1 0 4 1 0 1 1 0 2 0 11 6 2
AO 0 3 1 1 1 1 2 2 0 2 3 5 1 3 2 3 6 2 3
AP 0 1 4 3 2 2 0 0 4 0 7 3 2 0 0 0 4 2 1
AR 0 2 0 1 0 0 0 1 2 1 0 2 0 0 0 1 7 6 1
AW 0 1 0 0 3 1 0 1 0 0 0 0 5 1 4 3 3 0 3
AY 0 2 2 2 1 4 2 0 1 0 0 4 0 1 5 2 7 1 1
BC 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 25
BD 0 3 0 1 0 3 0 2 1 0 0 0 1 6 0 9 9 3 3
BE 0 0 0 2 0 0 0 1 0 0 0 0 0 8 6 0 9 2 8
MF 0 7 2 11 2 8 5 2 10 7 4 7 10 2 9 11 36 24 13
LF 0 1 0 1 1 1 5 2 4 3 1 0 3 3 2 3 24 8 7
EN 69 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
(ST-AB) 0 6 0 0 5 0 0 2 0 8 0 0 1 0 0 0 2 0 0
((ST-AB)AP) 0 1 0 2 0 1 0 0 0 0 2 1 0 0 0 0 1 0 0
(((ST-AB)AP)AE) 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0
Student Beliefs about Police Interviews
58
ST AA AB AE AF AG AH AI AO AP AR AW AY BC BD BE MF LF EN
(BC-EN)
(BE(BC-EN))
(AW(BE(BC-EN)))
(AO(AW(BE(BC-EN))))
ST 0 8 24 6 3 3 0 0 2 6 1 0 1 0 0 1 9 6 0 0 0 0 0
AA 0 0 2 8 4 7 10 5 1 2 2 2 5 0 3 1 9 2 0 0 0 0 0
AB 0 11 0 2 6 1 0 2 0 8 1 0 2 0 0 0 4 1 1 0 0 0 0
AE 0 7 0 0 3 3 12 1 0 1 3 0 0 2 2 1 8 3 0 2 0 0 0
AF 0 4 1 4 0 4 2 1 5 2 1 0 2 0 2 0 4 1 0 0 0 0 0
AG 0 4 0 1 1 0 6 11 6 0 0 1 2 3 2 0 5 0 1 2 0 0 0
AH 0 7 0 1 5 2 0 8 1 1 1 0 0 0 2 1 13 2 1 0 0 0 1
AI 0 2 2 2 1 3 1 0 4 1 0 1 1 0 2 0 11 6 2 0 0 0 1
AO 0 3 1 1 1 1 2 2 0 2 3 5 1 3 2 3 6 2 3 3 1 2 0
AP 0 1 4 3 2 2 0 0 4 0 7 3 2 0 0 0 4 2 1 0 0 0 0
AR 0 2 0 1 0 0 0 1 2 1 0 2 0 0 0 1 7 6 1 0 0 0 0
AW 0 1 0 0 3 1 0 1 0 0 0 0 5 1 4 3 3 0 3 1 2 0 0
AY 0 2 2 2 1 4 2 0 1 0 0 4 0 1 5 2 7 1 1 1 0 0 0
BC 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 25 0 0 0 0
BD 0 3 0 1 0 3 0 2 1 0 0 0 1 6 0 9 9 3 3 1 1 0 0
BE 0 0 0 2 0 0 0 1 0 0 0 0 0 8 6 0 9 2 8 6 0 0 0
MF 0 7 2 11 2 8 5 2 10 7 4 7 10 2 9 11 36 24 13 2 1 0 0
LF 0 1 0 1 1 1 5 2 4 3 1 0 3 3 2 3 24 8 7 3 1 0 0
EN 69 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0