Quantitative Resilience Quantitative Resilience Research across Cultures Research across Cultures

and Contexts and Contexts

Fons J. R. van de VijverFons J. R. van de Vijver

OutlineOutline 1. General introduction1. General introduction

• Tertium comparationisTertium comparationis Approaches: Absolutism/relativism/universalismApproaches: Absolutism/relativism/universalism

• Identity of meaningIdentity of meaning 2. Common problems of cross-cultural studies (and 2. Common problems of cross-cultural studies (and

their solutions)their solutions) 3. 3. Establishing similarity of meaning: Establishing similarity of meaning:

• 3a. Bias and equivalence: Taxonomies3a. Bias and equivalence: Taxonomies• 3b. Examples3b. Examples

4. Acculturation4. Acculturation• Concepts and Models / AssessmentConcepts and Models / Assessment

5. Test adaptations5. Test adaptations• Concepts / ExampleConcepts / Example

Conceptual core of cross-cultural studiesConceptual core of cross-cultural studies• Aim is to compare constructs or scoresAim is to compare constructs or scores

Is resilience the same across the globe?Is resilience the same across the globe? Is Country A more/less resilient than Country B?Is Country A more/less resilient than Country B?

• Comparison always implies some shared quality Comparison always implies some shared quality (tertium comparationis):(tertium comparationis):If a comparison visualizes an action, state, quality, If a comparison visualizes an action, state, quality, object, or a person by means of a parallel which is object, or a person by means of a parallel which is drawn to a different entity, the two things which are drawn to a different entity, the two things which are being compared do not necessarily have to be being compared do not necessarily have to be identical. However, they must possess at least one identical. However, they must possess at least one quality in common. This common quality has quality in common. This common quality has traditionally been referred to as traditionally been referred to as tertium comparationis tertium comparationis (Source: http://en.wikipedia.org/wiki/Tertium_comparationis)(Source: http://en.wikipedia.org/wiki/Tertium_comparationis)..

General IntroductionGeneral Introduction

Views on the Relation between Views on the Relation between Resilience and CultureResilience and Culture

1. 1. Absolutism (“etic”)Absolutism (“etic”)• Resilience refers to a universal set of characteristics that individuals Resilience refers to a universal set of characteristics that individuals

use to cope with and thrive despite adversityuse to cope with and thrive despite adversity 2. 2. RelativismRelativism

• Resilience refers to a concept (dealing with coping and thriving) that is Resilience refers to a concept (dealing with coping and thriving) that is universally applicable; however, its manifestations may differ across universally applicable; however, its manifestations may differ across culturescultures

• Example: Zimmerman & Brenner (2010, referring to Ungar, 2006)Example: Zimmerman & Brenner (2010, referring to Ungar, 2006) The conceptual foundation of resiliency theory can be applicable across cultures; The conceptual foundation of resiliency theory can be applicable across cultures;

the extent to which resources and assets are applied by youth in their experiences the extent to which resources and assets are applied by youth in their experiences of adversity, however, may not be consistent across all contexts. of adversity, however, may not be consistent across all contexts.

3. 3. Relativism (“emic”)Relativism (“emic”)• Resilience refers to basic concept of coping and thriving; however, Resilience refers to basic concept of coping and thriving; however,

link between resilience and cultural context is so close that cross-link between resilience and cultural context is so close that cross-cultural comparisons of resilience are futile and superficial cultural comparisons of resilience are futile and superficial

Choice between models is often made on Choice between models is often made on an ideological basisan ideological basis

However, more productive to see However, more productive to see absolutism and relativism as extremes absolutism and relativism as extremes along a continuumalong a continuum

Empirical studies possible of adequacy of Empirical studies possible of adequacy of these viewpointsthese viewpoints

Cross-cultural evidence is vital for Cross-cultural evidence is vital for determining which viewpoint holds for a determining which viewpoint holds for a particular measure/constructparticular measure/construct

Part 2Part 2 What are common problems What are common problems

in comparative studies?in comparative studies?•Central problem:Central problem:

Identity of meaningIdentity of meaning

Common methodological Common methodological problems of cross-cultural problems of cross-cultural

research and their solutionsresearch and their solutions

Problem 1Problem 1

Cross cultural differences in scores Cross cultural differences in scores cannot be interpreted due to rival cannot be interpreted due to rival hypotheses hypotheses • Particularly salient in two-culture studies Particularly salient in two-culture studies

that do not consider contextual factors that do not consider contextual factors Solution: Solution:

• Anticipate on rival hypotheses by Anticipate on rival hypotheses by including more cultures or measuring including more cultures or measuring contextual factors contextual factors

Problem 2 Problem 2

Cross-cultural similarities and differences Cross-cultural similarities and differences are visually (and not statistically) tested are visually (and not statistically) tested • A common example is the absence of a test of A common example is the absence of a test of

similarities of internal consistency coefficients similarities of internal consistency coefficients SolutionSolution

• Explicit tests of cross-cultural similarities and Explicit tests of cross-cultural similarities and differences; e.g., simple test of similarity of differences; e.g., simple test of similarity of independent reliabilities availableindependent reliabilities available

Test of Independent Reliabilities Test of Independent Reliabilities

1 and 2: the reliabilities (usually Cronbach's

of an instrument in two cultural groups.

Statistic (1-1 2) follows an F distribution

with N1 - 1 and N2 - 1 degrees of freedom (N1 and

N2 are the sample sizes).

Problem 3 Problem 3

Samples show confounding Samples show confounding differences differences • Particularly salient in convenience Particularly salient in convenience

sampling sampling Solution: Solution:

• Adaptation of study design and Adaptation of study design and assessment of confounding differences assessment of confounding differences

Problem 4 Problem 4 Means of different cultural groups are Means of different cultural groups are

compared without assessing the equivalence compared without assessing the equivalence • Particularly salient when studying new Particularly salient when studying new

instruments or working with cultures in which instruments or working with cultures in which instrument has not been used instrument has not been used

Solution: Solution: • Assessment of structural and metric equivalence; Assessment of structural and metric equivalence;

assessment of structural equivalence/differential assessment of structural equivalence/differential item functioning should be a routine part of item functioning should be a routine part of analysis, similar to routine assessment of internal analysis, similar to routine assessment of internal consistency consistency

Problem 5 Problem 5 Cultural characteristics are attributed to all Cultural characteristics are attributed to all

individuals of that culture (ecological fallacy) individuals of that culture (ecological fallacy) • Particularly common in studies of individualism—Particularly common in studies of individualism—

collectivism collectivism Solution:Solution:

• Awareness of distinction between individual-and Awareness of distinction between individual-and culture-level characteristicsculture-level characteristics

• Assessment of relevant characteristics, such as Assessment of relevant characteristics, such as individualism—collectivism, at individual level individualism—collectivism, at individual level

Problem 6 Problem 6

No check on quality of translation/ No check on quality of translation/ adaptation adaptation • Check is often not reported or procedure is Check is often not reported or procedure is

poorly specified (e.g., translation back poorly specified (e.g., translation back translation has been used, but results of translation has been used, but results of procedure are not reported)procedure are not reported)

Solution: Solution: • Awareness that translation back translation is not Awareness that translation back translation is not

always the best possible method; other always the best possible method; other approaches, such as committee approach, may approaches, such as committee approach, may be more suitable be more suitable

• More detail in reports about More detail in reports about translation/adaptation procedure translation/adaptation procedure

Problem 7 Problem 7

Lack of rationale for selecting Lack of rationale for selecting cultures cultures • Convenience sampling of cultures is by Convenience sampling of cultures is by

far the most common procedure in far the most common procedure in cross-cultural psychology; most common cross-cultural psychology; most common comparison is between Japan and the UScomparison is between Japan and the US

Solution: Solution: • Explain why the culture was chosen Explain why the culture was chosen

Problem 8 Problem 8

There is a verification bias in studies There is a verification bias in studies of common paradigms of common paradigms • Particularly salient in studies of Particularly salient in studies of

individualism –collectivism individualism –collectivism Solution:Solution:

• More critical appreciation of the More critical appreciation of the boundaries of the construct, more focus boundaries of the construct, more focus on falsification on falsification

Problem 9 Problem 9 There is a focus on the statistical significance of There is a focus on the statistical significance of

cross-cultural differences cross-cultural differences • In the first and two related problems: In the first and two related problems:

Implicit goal of cross-cultural psychology is not the Implicit goal of cross-cultural psychology is not the establishment of cross-cultural differences establishment of cross-cultural differences

Focus on significance detracts attention from effect sizes Focus on significance detracts attention from effect sizes

Solution: Solution: • Balanced treatment of similarities and differences; Balanced treatment of similarities and differences;

differences easier to interpret against a backdrop of differences easier to interpret against a backdrop of similarities similarities

• More effect sizes should be reported, such as Cohen’s More effect sizes should be reported, such as Cohen’s dd and (partial) eta squares.and (partial) eta squares.

Problem 10 Problem 10 Results are generalized to large populations, Results are generalized to large populations,

often complete populations of countries, often complete populations of countries, although no probability sampling has been although no probability sampling has been employed to recruit participants employed to recruit participants • Particularly salient in convenience sampling of Particularly salient in convenience sampling of

participants (often student samples)participants (often student samples) SolutionSolution

• More attention in reports for sampling frame and More attention in reports for sampling frame and for consequences on external validity for consequences on external validity

Part 3aPart 3a Bias and equivalence: Bias and equivalence:

• Definitions of concepts Definitions of concepts • A framework A framework

(a) Bias and Equivalence(a) Bias and Equivalence

Does the test measure the same Does the test measure the same attributes for all cultural groups?attributes for all cultural groups?

Can scores be compared across Can scores be compared across ethnic groups?ethnic groups?

Bias: TaxonomyBias: Taxonomy

What is internal bias?What is internal bias?• GeneralGeneral: dissimilarity of psychological meaning : dissimilarity of psychological meaning

across cultural groupsacross cultural groups• PracticalPractical: when cross-cultural differences do : when cross-cultural differences do

not involve target construct measured by the not involve target construct measured by the testtest

• TheoreticalTheoretical: a cross-cultural comparison is : a cross-cultural comparison is biased when observed cross-cultural differences biased when observed cross-cultural differences (in structure or level) cannot be fully interpreted (in structure or level) cannot be fully interpreted in terms of the domain of interestin terms of the domain of interest

Taxonomy of BiasTaxonomy of Bias

Type Source

Construct bias Theoretical construct

Method bias Measurement aspects (e.g., sample, test, administration)

Item bias Specific item aspects (e.g., poor translation)

Construct BiasConstruct Bias

Partial nonoverlap of behaviors defining Partial nonoverlap of behaviors defining constructconstruct• González Castro & Murray (2010): Criteria González Castro & Murray (2010): Criteria

for resilience are based on studies with U.S. for resilience are based on studies with U.S. youth and adults, and one important cross-youth and adults, and one important cross-cultural issue involves how these criteria, cultural issue involves how these criteria, as Westernized aspects of resilience, may as Westernized aspects of resilience, may or may not relate to resilience that is or may not relate to resilience that is manifest in underdeveloped and/or non-manifest in underdeveloped and/or non-Western countries.Western countries.

• Definition of happiness in Definition of happiness in individualistic and collectivistic individualistic and collectivistic countries?countries?

Example: Uchida, Norasakkunkit and Example: Uchida, Norasakkunkit and Kitayama (2004):Kitayama (2004):

Types and Sources of Method BiasTypes and Sources of Method Bias

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Method bias tends to have a global influence on cross-Method bias tends to have a global influence on cross-cultural score differences (e.g., increment due to social cultural score differences (e.g., increment due to social desirability)desirability)

Item BiasItem Bias(also known as differential item (also known as differential item functioning, DIF)functioning, DIF)

Informal description Informal description Differences in psychological meaning of Differences in psychological meaning of stimuli, due to anomalies at item levelstimuli, due to anomalies at item level

More formal definition:More formal definition:An item of a scale (e.g., measuring anxiety) An item of a scale (e.g., measuring anxiety) is said to be biased if persons with the same is said to be biased if persons with the same trait anxiety, but coming from different trait anxiety, but coming from different cultures, are not equally likely to endorse cultures, are not equally likely to endorse the item. the item.

Example of Biased ItemExample of Biased Item

0

0.2

0.4

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1 2 3 4 5 6

Total test score

Mea

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core

Culture ACulture B

Types of (un)biased items

(a) Unbiased item

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Very low Low Medium High Very high

Score level

Mea

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core

Culture A Culture B

(b) Item with uniform bias

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Very low Low Medium High Very high

Score level

Mea

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core

Culture A Culture B

(c) Item with non-uniform bias

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Very low Low Medium High Very high

Score level

Mea

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Culture A Culture B

(d) Item with both uniform and non-uniform bias

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Very low Low Medium High Very high

Score level

Me

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Culture A Culture B

Analysis of Variance and Item BiasAnalysis of Variance and Item Bias Item behavior examined per itemItem behavior examined per item We We do not do not test for cultural test for cultural

differences, but we test whether differences, but we test whether scores are identical for scores are identical for persons from different groups persons from different groups with an equal proficiencywith an equal proficiency

Note: regression approach quite Note: regression approach quite similar (illustrated later)similar (illustrated later)

Taxonomy of Taxonomy of EquivalenceEquivalence

Refers to level of comparabilityRefers to level of comparability Is related to bias:Is related to bias:

Highest level of equivalence obtained Highest level of equivalence obtained for bias-free measurementfor bias-free measurement

Types of EquivalenceTypes of EquivalenceThree types:Three types:

•1. 1. ““StructuralStructural”” or or ““functional functional equivalenceequivalence””

•2. 2. ““Metric equivalenceMetric equivalence” or ” or ““measurement unit equivalencemeasurement unit equivalence””

•3. 3. ““Scalar equivalenceScalar equivalence”” or or ““full full score equivalencescore equivalence””

(a) “Structural” or “Functional (a) “Structural” or “Functional Equivalence”Equivalence”

Measurement of the same traitsMeasurement of the same traits Various statistical tools available, e.g.,Various statistical tools available, e.g.,

• exploratory factor analysis (with target rotation)exploratory factor analysis (with target rotation)• confirmatory factor analysisconfirmatory factor analysis• nomological networks (particularly relevant when nomological networks (particularly relevant when

items/questions are not identical across cultures)items/questions are not identical across cultures) Qualitative equivalence can be firmly Qualitative equivalence can be firmly

establishedestablished

(b) “Metric Equivalence”, (b) “Metric Equivalence”, “Measurement Unit Equivalence”“Measurement Unit Equivalence”

Difference in offset of scales of cultural Difference in offset of scales of cultural groups, equal measurement unitsgroups, equal measurement units

Individual differences have a different Individual differences have a different meaning meaning withinwithin and and acrossacross cultures: cultures:

no problems with offset in intra-cultural no problems with offset in intra-cultural comparison, offset has to be added in cross-comparison, offset has to be added in cross-cultural comparisoncultural comparison

Statistical tool: structural equation Statistical tool: structural equation modeling (confirmatory factor analysis)modeling (confirmatory factor analysis)

(c) “Scalar Equivalence” or (c) “Scalar Equivalence” or “Full Score Equivalence”“Full Score Equivalence”

Complete comparability of scores, Complete comparability of scores, both within and across cultures; both within and across cultures; seamless transfer of scores across seamless transfer of scores across culturescultures

Frequently taken as the aim of Frequently taken as the aim of cross-cultural researchcross-cultural research

Comparability and Equivalence Comparability and Equivalence LevelsLevels

EquivalencEquivalencee

ComparabilityComparability

StructuralStructural Underlying constructUnderlying construct

MetricMetric Same plusSame plus score metric score metric

ScalarScalar Same plusSame plus origin of origin of scalescale

Part 3bPart 3b

Establishing similarity of meaningEstablishing similarity of meaning• How to determine equivalence?How to determine equivalence?• How to determine item bias?How to determine item bias?

Many statistical procedures available Many statistical procedures available for testing structural equivalencefor testing structural equivalence

Common approach:Common approach:• Apply dimensionality-reduction Apply dimensionality-reduction

technique technique • Compare underlying dimensions across Compare underlying dimensions across

culturescultures• Similarity of underlying dimensions is Similarity of underlying dimensions is

criterion for similarity of meaningcriterion for similarity of meaning

Testing Testing Structural Structural EquivalenceEquivalence: :

Exploratory Exploratory Factor AnalysisFactor Analysis

Two procedures explainedTwo procedures explained•1. 1. Pairwise comparisonsPairwise comparisons

Compare all cultures in a Compare all cultures in a pairwise mannerpairwise manner

•2. “2. “One to all” comparisonOne to all” comparison Compare all cultures to a global, Compare all cultures to a global, pooled solutionpooled solution

• Characteristics of Characteristics of pairwisepairwise comparisons comparisons Strong point: much detail, all pairs comparedStrong point: much detail, all pairs compared Weak point: computationally cumbersome, Weak point: computationally cumbersome,

difficult to integratedifficult to integrate

• Characteristics of Characteristics of pooledpooled comparisons comparisons Strong point: maintains overview, integrationStrong point: maintains overview, integration Weak point: can conceal subgroups of Weak point: can conceal subgroups of

countriescountries

Example PairwiseExample Pairwise Data set: WISC-III administered in Data set: WISC-III administered in

Canada and Netherlands/FlandersCanada and Netherlands/Flanders

SampleSamplemale female

age Belgium/NethCanada Belgium/NethCanada6 56 50 54 507 46 50 56 508 66 50 58 509 55 50 53 50

10 59 50 60 5011 53 50 60 5012 47 50 57 5013 48 50 53 5014 62 50 63 5015 53 50 56 5016 54 50 56 50

12 Subtests12 Subtests1.1. Picture CompletionPicture Completion2.2. InformationInformation3.3. CodingCoding4.4. SimilaritiesSimilarities5.5. Picture ArrangementPicture Arrangement6.6. ArithmeticArithmetic7.7. Block DesignBlock Design8.8. VocabularyVocabulary9.9. Object AssemblyObject Assembly10.10. ComprehensionComprehension11.11. Symbol SearchSymbol Search 12.12. Digit SpanDigit Span

Analysis StepsAnalysis Steps

1.1. Determine number of factors in Determine number of factors in combined samplecombined sample

2.2. Carry out factor analyses per groupCarry out factor analyses per group

3.3. Compare factors across groupsCompare factors across groups

Note: analysis of scaled scoresNote: analysis of scaled scores

1. Determining Number of 1. Determining Number of FactorsFactorsScree Plot

Component Number

13121110987654321

Eig

en

valu

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6

5

4

3

2

1

0

1. Determining Number of Factors1. Determining Number of Factors

Scree plot suggests the extraction of Scree plot suggests the extraction of a single factora single factor

Literature:Literature:• Debate about 3 or 4 factorsDebate about 3 or 4 factors• Hierarchical model of correlated factorsHierarchical model of correlated factors

Here: 4 factorsHere: 4 factors

2. Factor Analyses per group: 2. Factor Analyses per group: Oblimin-Rotated SolutionOblimin-Rotated Solution

Componentcountry = Belgium/Neth 1 2 3 4Scaled score for picture completion 0.15 -0.05 -0.73 -0.16Scaled score for information 0.79 0.03 0.00 0.07Scaled score for coding -0.02 0.92 0.04 -0.05Scaled score for similarities 0.77 0.02 -0.10 -0.06Scaled score for picture arrangement 0.10 0.13 -0.61 -0.04Scaled score for arithmetic 0.58 0.13 -0.10 0.16Scaled score for block design 0.06 0.12 -0.62 0.27Scaled score for vocabulary 0.87 -0.03 0.00 0.02Scaled score for object assembly -0.05 0.00 -0.76 0.16Scaled score for comprehension 0.78 -0.06 -0.05 -0.11Scaled score for symbol search -0.02 0.85 -0.10 -0.02Scaled score for digit span 0.37 0.14 0.17 0.54Scaled score for mazes -0.10 -0.07 -0.19 0.82

2. Factor Analyses per 2. Factor Analyses per group: Oblimin-Rotated group: Oblimin-Rotated

SolutionSolutioncountry = Canada 1 2 3 4Scaled score for picture completion 0.38 0.04 -0.37 -0.31Scaled score for information 0.86 -0.09 -0.02 0.08Scaled score for coding -0.09 0.94 0.10 0.05Scaled score for similarities 0.82 0.00 -0.03 -0.04Scaled score for picture arrangement 0.34 0.26 -0.15 -0.37Scaled score for arithmetic 0.52 0.13 -0.25 0.32Scaled score for block design 0.11 0.27 -0.62 -0.09Scaled score for vocabulary 0.92 -0.05 0.07 0.03Scaled score for object assembly 0.14 0.11 -0.57 -0.30Scaled score for comprehension 0.74 0.07 0.09 -0.01Scaled score for symbol search -0.01 0.83 -0.07 0.03Scaled score for digit span 0.31 0.21 -0.14 0.69Scaled score for mazes -0.13 -0.11 -0.88 0.19

3. Compare Factors across 3. Compare Factors across GroupsGroups

Rotate one solution to the otherRotate one solution to the other• Target rotations to deal with rotational Target rotations to deal with rotational

freedom in factor analysisfreedom in factor analysis Evaluation by means of Tucker’s phi Evaluation by means of Tucker’s phi

(factor congruence coefficient):(factor congruence coefficient):• similarity of factors up to multiplying similarity of factors up to multiplying

(positive) constant (correct for (positive) constant (correct for differences in eigenvalues across differences in eigenvalues across cultures)cultures)

3. Compare Factors across 3. Compare Factors across GroupsGroups

Formula (Formula (xx and and yy are loadings after are loadings after target rotation of one to the other):target rotation of one to the other):

22ii

ii

yx

yx

3. Compare Factors across 3. Compare Factors across GroupsGroups

original sum multiplication-0.2 0.2 -0.40.2 0.6 0.40.3 0.7 0.60.4 0.8 0.8

phi 0.858474 1

3. Compare Factors across 3. Compare Factors across GroupsGroups

Values above .90 are usually Values above .90 are usually considered to be adequate and considered to be adequate and values above .95 to be excellentvalues above .95 to be excellent

Such high values point to similarity of Such high values point to similarity of factors factors structural equivalence structural equivalence

3. Compare Factors across 3. Compare Factors across GroupsGroups

Dedicated software needed to Dedicated software needed to compute Tucker’s phicompute Tucker’s phi

SPSS routine availableSPSS routine available

FACTOR LOADINGS AFTER TARGET ROTATIONpictcomp 0.31 0.07 -0.38 -0.59informat 0.77 0.02 0.03 0.21coding -0.06 0.9 0.13 0.12similari 0.78 0.03 0.04 0.05pictarra 0.22 0.22 -0.38 -0.4arithmet 0.57 0.14 -0.12 0.17blockdes 0.16 0.2 -0.6 -0.2vocabula 0.85 -0.04 0.06 0.17objecass 0.09 0.12 -0.64 -0.42comprehe 0.78 -0.05 0.11 0.03symbsear -0.03 0.86 0 0.04digitspa 0.28 0.08 -0.23 0.58mazes -0.12 -0.08 -0.73 0.41

Belg./Neth. rotated

DIFFERENCE IN LOADINGS AFTER TARGET ROTATION-0.07 0.04 -0.01 -0.28-0.09 0.11 0.05 0.130.04 -0.04 0.03 0.07

-0.05 0.03 0.08 0.09-0.12 -0.03 -0.22 -0.030.05 0 0.12 -0.140.05 -0.06 0.01 -0.11

-0.07 0.02 -0.01 0.15-0.05 0 -0.07 -0.120.04 -0.12 0.02 0.04

-0.02 0.03 0.07 0.01-0.04 -0.14 -0.09 -0.110.01 0.02 0.15 0.22

PROPORTIONALITY COEFFICIENT per Factor:

.99 .98 .97 .91

ConclusionConclusion

Strong evidence for similarity of first Strong evidence for similarity of first two factorstwo factors

Less convincing for third and fourth Less convincing for third and fourth factorfactor

5656

Example “One to All”Example “One to All” Steps in analysis:Steps in analysis:

• 1. Exploratory factor analysis on the total 1. Exploratory factor analysis on the total data set;data set;

Two procedures (Two procedures (note: correct for mean note: correct for mean differences between groupsdifferences between groups):):

• ““quick and dirty”: standardize scores per cultural quick and dirty”: standardize scores per cultural groups and factor analyze the standardized scoresgroups and factor analyze the standardized scores

• more adequate solution: compute the weighted more adequate solution: compute the weighted average of the covariance matrices of the cultural average of the covariance matrices of the cultural groups (weight by sample size) groups (weight by sample size)

this factor analysis provides the “pooled this factor analysis provides the “pooled solution”solution”

““One-to-all” procedureOne-to-all” procedure

2. Carry out a factor analysis in each 2. Carry out a factor analysis in each cultural groupcultural group

3. Compute agreement of the pooled 3. Compute agreement of the pooled solution and each of the country solution and each of the country solutionssolutions

Source: Van de Vijver, F.J.R. & Poortinga, Y.H. (2002). Structural Equivalence in Multilevel Research. Journal of Cross-Cultural Psychology.

ExampleExample 1990-1991 World Values Survey (Inglehart, 1993, 1997)1990-1991 World Values Survey (Inglehart, 1993, 1997) 47,871 respondents from the following 39 “regions” (number 47,871 respondents from the following 39 “regions” (number

of respondents in parentheses): Austria (1355), Belarus (912), of respondents in parentheses): Austria (1355), Belarus (912), Belgium (2318), Brazil (1672), Bulgaria (877), Canada (1545), Belgium (2318), Brazil (1672), Bulgaria (877), Canada (1545), Chile (1368), China (960), (the former) Czechoslovakia (1384), Chile (1368), China (960), (the former) Czechoslovakia (1384), Denmark (892), (the former) East Germany (1226), Estonia Denmark (892), (the former) East Germany (1226), Estonia (864), Finland (416), France (902), Hungary (886), Iceland (864), Finland (416), France (902), Hungary (886), Iceland (659), India (2150), Ireland (976), Italy (1810), Japan (655), (659), India (2150), Ireland (976), Italy (1810), Japan (655), Latvia (720), Lithuania (847), Mexico (1193), Moscow (894), Latvia (720), Lithuania (847), Mexico (1193), Moscow (894), Netherlands (935), Nigeria (954), Northern Ireland (283), Netherlands (935), Nigeria (954), Northern Ireland (283), Norway (1111), Poland (850), Portugal (976), Russia (1642), Norway (1111), Poland (850), Portugal (976), Russia (1642), South Africa (2480), South Korea (1210), Spain (3408), South Africa (2480), South Korea (1210), Spain (3408), Sweden (901), Turkey (886), United Kingdom (1356), United Sweden (901), Turkey (886), United Kingdom (1356), United States (1688), and (the former) West Germany (1710).States (1688), and (the former) West Germany (1710).

InstrumentInstrument Item Dimension

Making sure this country has strong

defense forces

Materialism

Seeing that people have more to say

about how things are done at their jobs

and in their communities

Postmaterialism

Trying to make our cities and countryside

more beautiful

Postmaterialism

Maintaining order in the nation Materialism

Giving people more to say in important

government decisions

Postmaterialism

Protecting freedom of speech Postmaterialism

A stable economy Materialism

Progress toward a less impersonal and

more humane society

Postmaterialism

Progress toward a society in which ideas

count more than money

Postmaterialism

Pooled solutionPooled solutionItem Within

Defense -.30

Democracy1 .56

Cities .02

Order -.67

Democracy2 .57

Free speech .31

Econ. Stab. -.63

Humane .54

Ideas .43

Eigenvalue (percentage explained) 2.14

(23.9%)

(Sign of loadings in line with expectation)

Stem-and-Leaf Display of Agreement Pooled Stem-and-Leaf Display of Agreement Pooled Loadings and Factor Loadings per CountryLoadings and Factor Loadings per CountryStem Leaf

.99 01346

.98 00012566667

.97 56789

.96 36

.95 068

.94 227

.93 249

.92 4

.91 8

.90 348

.89 1

.57 (Extreme)

Each leaf represents one observation (country)

Correlations of GNP and the Loadings per Correlations of GNP and the Loadings per Region on the Postmaterialism ScaleRegion on the Postmaterialism Scale

Item Correlation

Defense .06

Democracy1 -.26

Cities .51**

Order .59***

Democracy2 -.60***

Free speech -.09

Econ. Stab. -.50**

Humane .52***

Ideas .47**

Conclusion: Postmaterialism concept more salient in more affluent countries

Metric Metric EquivalenceEquivalence at Scale Levelat Scale Level: :

Structural Equation Structural Equation ModelingModeling

Difference with Exploratory Factor Difference with Exploratory Factor AnalysesAnalyses

Starts from covariance matricesStarts from covariance matrices• Use metric informationUse metric information

More parameters tested for cross-cultural More parameters tested for cross-cultural similarity; examplessimilarity; examples• Factor loadingsFactor loadings• Factor correlations/covariancesFactor correlations/covariances• Error component of latent variablesError component of latent variables• Error component of observed variablesError component of observed variables

Enables the testing of a hierarchy of Enables the testing of a hierarchy of modelsmodels

Example of AMOSExample of AMOS Model tested: one factor of verbal Model tested: one factor of verbal

comprehension factor in two countries comprehension factor in two countries (Belgium/Netherlands and Canada)(Belgium/Netherlands and Canada)

Models tested:Models tested:• Identical factor loadings across countriesIdentical factor loadings across countries• Free factor loadingsFree factor loadings• Idem with a correlated errorIdem with a correlated error

For diagram and output: see AMOS filesFor diagram and output: see AMOS files

Basic ModelBasic Model

intelligence

COMPREHEe51

VOCABULAe41

ARITHMETe31

SIMILARIe21

INFORMATe11

1

e61

Use of multiple group optionUse of multiple group option

Measurement weights: Measurement weights: regression regression weights in the measurement part of the weights in the measurement part of the model. In the case of a factor analysis model. In the case of a factor analysis model, these are the "factor loadings".model, these are the "factor loadings".

Structural residuals: Structural residuals: variances and variances and covariances of residual (error) variables in covariances of residual (error) variables in the structural part of the model.the structural part of the model.

Measurement residualsMeasurement residuals: variances and : variances and covariances of residual (error) variables in covariances of residual (error) variables in the measurement part of the model. the measurement part of the model.

AMOS modelAMOS model

intelligence

COMPREHEe5

d

1

VOCABULAe4

c

1

ARITHMETe3

b

1

SIMILARIe2a1

INFORMATe11

1

e61

Measurement weightsMeasurement weights

AMOS modelAMOS model

intelligence

COMPREHEe5

d

1

VOCABULAe4

c

1

ARITHMETe3

b

1

SIMILARIe2a1

INFORMATe11

1

e6e61

Structural residualsStructural residuals

AMOS modelAMOS model

intelligence

COMPREHEe5e5

d

1

VOCABULAe4e4

c

1

ARITHMETe3e3

b

1

SIMILARIe2e2a1

INFORMATe1e11

1

e61

Measurement residualsMeasurement residuals

BelgNeth - BelgNeth - UnconstrainedUnconstrained

Estimate S.E. C.R. P Label

COMPREHE <--- intelligence .952 .042 22.661 *** a1_1

VOCABULA <--- intelligence 1.144 .043 26.736 *** a2_1

ARITHMET <--- intelligence .801 .036 22.415 *** a3_1

SIMILARI <--- intelligence 1.031 .042 24.720 *** a4_1

INFORMAT <--- intelligence 1.000

Regression Weights: (Canada - Unconstrained)

CanadaCanada Estimate S.E. C.R. P Label

COMPREHE <--- intelligence .874 .040 21.770 *** a1_2

VOCABULA <--- intelligence 1.158 .041 28.323 *** a2_2

ARITHMET <--- intelligence .780 .038 20.796 *** a3_2

SIMILARI <--- intelligence 1.056 .039 26.886 *** a4_2

INFORMAT <--- intelligence 1.000

CMIN

ModelModel NPARNPAR CMINCMIN DFDF PP CMIN/DFCMIN/DF

UnconstrainedUnconstrained 2222 47.98247.982 88 .000.000 5.9985.998

Measurement weightsMeasurement weights 1818 51.79351.793 1212 .000.000 4.3164.316

Structural residualsStructural residuals 1717 53.04953.049 1313 .000.000 4.0814.081

Measurement Measurement residualsresiduals

1111 66.73266.732 1919 .000.000 3.5123.512

Saturated modelSaturated model 3030 .000.000 00

Independence modelIndependence model 1010 5084.1045084.104 2020 .000.000 254.205254.205

RMR, GFI

Model RMR GFI AGFI PGFI

Unconstrained .157 .992 .970 .265

Measurement weights .185 .991 .978 .397

Structural residuals .241 .991 .979 .429

Measurement residuals

.227 .988 .982 .626

Saturated model .000 1.000

Independence model 4.034 .450 .175 .300

RMSEA

Model RMSEA LO 90 HI 90 PCLOSE

Unconstrained .046 .034 .059 .658

Measurement weights .038 .028 .049 .969

Structural residuals .036 .027 .047 .985

Measurement residuals

.033 .025 .042 1.000

Independence model .330 .322 .338 .000

Nested Model Comparisons

Assuming model Unconstrained to be correct:

Model DF CMIN P NFI

Delta-1 IFI

Delta-2 RFI

rho-1 TLI

rho2 Measurement weights 4 3.811 .432 .001 .001 -.007 -.007 Structural residuals 5 5.067 .408 .001 .001 -.008 -.008 Measurement residuals 11 18.750 .066 .004 .004 -.010 -.010

Assuming model Measurement weights to be correct:

Model DF CMIN P NFI

Delta-1 IFI

Delta-2 RFI

rho-1 TLI

rho2 Structural residuals 1 1.256 .262 .000 .000 -.001 -.001 Measurement residuals 7 14.939 .037 .003 .003 -.003 -.003

Assuming model Structural residuals to be correct:

Model DF CMIN P NFI

Delta-1 IFI

Delta-2 RFI

rho-1 TLI

rho2 Measurement residuals 6 13.683 .033 .003 .003 -.002 -.002

Metric Metric EquivalenceEquivalence at Item Levelat Item Level: :

Item Bias Analysis/ Item Bias Analysis/

Differential Item Differential Item Functioning (DIF)Functioning (DIF)

Hundreds of statistical procedures availableHundreds of statistical procedures available Assumption: Assumption:

• Equal observed scores on global instrument (scale) in Equal observed scores on global instrument (scale) in different cultures have the same meaningdifferent cultures have the same meaning

Almost all techniques start from unidimensional Almost all techniques start from unidimensional scalesscales

Procedures test whether, given equal total scores, Procedures test whether, given equal total scores, patterns of observed scores are the same across patterns of observed scores are the same across culturescultures

Often applied proceduresOften applied procedures• ANOVA (example follows)ANOVA (example follows)• Item Response TheoryItem Response Theory• (in education) Mantel-Haenszel (equivalent to testing (in education) Mantel-Haenszel (equivalent to testing

applicability of Rasch model)applicability of Rasch model)

How to Determine Item Bias?How to Determine Item Bias?

Analysis of varianceAnalysis of variance INPUT: a data matrix with interval-INPUT: a data matrix with interval-

level dependent variables (e.g., level dependent variables (e.g., Likert-scale), one variable Likert-scale), one variable indicating culture.indicating culture.

Step 1: Compute Total ScoreStep 1: Compute Total Score

Compute total test score (or mean Compute total test score (or mean item score) (so, a unifactorial scale is item score) (so, a unifactorial scale is assumed).assumed).

COMPUTE sumscore = i_acad_1 + i_cult_1 + i_groo_1 + COMPUTE sumscore = i_acad_1 + i_cult_1 + i_groo_1 + i_infl_1 + i_inte_1 + i_like_1 + i_look_1 .i_infl_1 + i_inte_1 + i_like_1 + i_look_1 .

EXECUTE .EXECUTE .

Step 2: Determine CutoffsStep 2: Determine Cutoffs (here three groups; percenti(here three groups; percentilles 33 and 67).es 33 and 67).EXAMINEEXAMINE VARIABLES=sumscoreVARIABLES=sumscore /PLOT BOXPLOT STEMLEAF/PLOT BOXPLOT STEMLEAF /COMPARE GROUP /PERCENTILES(33, 67) HAVERAGE/COMPARE GROUP /PERCENTILES(33, 67) HAVERAGE /STATISTICS DESCRIPTIVES/STATISTICS DESCRIPTIVES /CINTERVAL 95 /CINTERVAL 95 /MISSING LISTWISE/MISSING LISTWISE /NOTOTAL. /NOTOTAL.

OROR

FREQUENCIESFREQUENCIES VARIABLES=sumscoreVARIABLES=sumscore /NTILES= 3/NTILES= 3 /ORDER= ANALYSIS ./ORDER= ANALYSIS .

Step 3: Compute LevelStep 3: Compute Level

RECODERECODE

sumscoresumscore

(Lowest thru 48=1) (49 thru 57=2) (58 thru (Lowest thru 48=1) (49 thru 57=2) (58 thru Highest=3) (ELSE=SYSMIS)Highest=3) (ELSE=SYSMIS)

INTO level .INTO level .

VARIABLE LABELS level 'Score level'.VARIABLE LABELS level 'Score level'.

EXECUTE .EXECUTE .

Step 4: Carry out ANOVAsStep 4: Carry out ANOVAs

UNIANOVAUNIANOVA i_acad_1 i_cult_1 i_groo_1 i_infl_1 i_inte_1 i_like_1 i_look_1 BY group leveli_acad_1 i_cult_1 i_groo_1 i_infl_1 i_inte_1 i_like_1 i_look_1 BY group level /METHOD = SSTYPE(3)/METHOD = SSTYPE(3) /INTERCEPT = INCLUDE/INTERCEPT = INCLUDE /PRINT = DESCRIPTIVE ETASQ/PRINT = DESCRIPTIVE ETASQ /CRITERIA = ALPHA(.05)/CRITERIA = ALPHA(.05) /DESIGN = group level group*level ./DESIGN = group level group*level .

Significant main effect of level: irrelevantSignificant main effect of level: irrelevant Significant main effect of culture: uniform biasSignificant main effect of culture: uniform bias Significant interaction between culture and level: nonuniform Significant interaction between culture and level: nonuniform

biasbias NOTE: in large samples effect sizes can be used (eta squared > NOTE: in large samples effect sizes can be used (eta squared >

.06: Cohen’s medium effect size).06: Cohen’s medium effect size)

RegressionRegression

DESCRIPTIVES VARIABLES=sumscore DESCRIPTIVES VARIABLES=sumscore cultcult

/STATISTICS=MEAN STDDEV MIN /STATISTICS=MEAN STDDEV MIN MAX.MAX.

* compute predictor values for these new * compute predictor values for these new variables.variables.

compute dev_mean=sumscore-52.6091.compute dev_mean=sumscore-52.6091.

compute dev_cult=cult-1.4473.compute dev_cult=cult-1.4473.

EXECUTE .EXECUTE .

compute interaction = dev_mean*dev_cult.compute interaction = dev_mean*dev_cult.

EXECUTE .EXECUTE .

REGRESSIONREGRESSION

/MISSING LISTWISE/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA/STATISTICS COEFF OUTS R ANOVA

/CRITERIA=PIN(.05) POUT(.10)/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN /NOORIGIN

/DEPENDENT i_acad_1/DEPENDENT i_acad_1

/METHOD=ENTER sumscore/METHOD=ENTER sumscore

/METHOD=ENTER cult/METHOD=ENTER cult

/METHOD=ENTER interaction./METHOD=ENTER interaction.

Part 4. AcculturationPart 4. Acculturation

Definition:Definition:Acculturation Acculturation refers to changes that refers to changes that take place as a result of continuous first-take place as a result of continuous first-hand contact between individuals of hand contact between individuals of different cultural origins different cultural origins (Redfield, Linton, & (Redfield, Linton, & Herskovits, 1936).Herskovits, 1936).

Psychological acculturation Psychological acculturation refers to psychological aspects of processrefers to psychological aspects of process

• Acculturation research Acculturation research traditions:traditions:

Stress and copingStress and coping Social learning Social learning

Social cognition (more Social cognition (more recent)recent)

Framework of Acculturation:Framework of Acculturation:Acculturation VariablesAcculturation Variables

Acculturation Conditions

Acculturation Outcomes

Cultural adoption

Cultural maintenance

Acculturation Orientations

Psychological well-being

(psychological distress, mood

states, feelings of acceptance, and

satisfaction)Sociocultural

competence in ethnic culture(interaction with

conationals, maintenance of

culturally appropriate skills and behaviors)

Characteristics of the receiving society (e.g., discrimination,

opportunity structures)

Characteristics of the society of

origin (objective, perceived)

Personal characteristics

Characteristics of the immigrant

group (objective, perceived)

Socioculturalcompetence in

mainstream culture

(interaction with hosts, acquisition of

culturally appropriate skills and behaviors)

FeaturesFeatures Compare S-O-R modelCompare S-O-R model Mediation model with feedback loopsMediation model with feedback loops

• Feedback almost never studiedFeedback almost never studied• Causality usually inferred (so, some Causality usually inferred (so, some

arbitrariness)arbitrariness) Implicit schemeImplicit scheme

• distal—proximal—outputdistal—proximal—output Term adaptation used in literature to refer Term adaptation used in literature to refer

to adjustment/outputto adjustment/output• Problem: adaptation can refer to both Problem: adaptation can refer to both

product and processproduct and process

Resilience-Related Pathways for Immigrants Resilience-Related Pathways for Immigrants ((González Castro & Murray, 2010González Castro & Murray, 2010))

Studies of Acculturation ConditionsStudies of Acculturation Conditions

Personality often studiedPersonality often studied• MPQ, Big Five MPQ, Big Five

Usually: extraversion +, neuroticism –Usually: extraversion +, neuroticism – Intelligence not studiedIntelligence not studied Multiculturalism policies presumably Multiculturalism policies presumably

unrelated to acculturation outcomes in unrelated to acculturation outcomes in Western societiesWestern societies• ESS (Schalk-Soekar et al., 2007)ESS (Schalk-Soekar et al., 2007)• ICSEY (Berry et al., 2006)ICSEY (Berry et al., 2006)

2 examples2 examples• Perceived acculturation contextPerceived acculturation context• Perceived cultural distancePerceived cultural distance

Structure of Perceived EnvironmentStructure of Perceived Environment

Mainstream context:

Minority context:

Role of (perceived) cultural distance

Psychological measures of distance (perceived Psychological measures of distance (perceived cultural distance) load on a single factorcultural distance) load on a single factor• Note: models of cross-cultural distance models Note: models of cross-cultural distance models

tend to be multidimensional (e.g., Hofstede) tend to be multidimensional (e.g., Hofstede)

Dimensionality of Cultural Dimensionality of Cultural DistanceDistance

Acculturation Orientations

Notes on terminology:Notes on terminology:

1. Various terms used, e.g.,1. Various terms used, e.g.,

Strategies, styles, orientationsStrategies, styles, orientations

2. Adaptation usually reserved for 2. Adaptation usually reserved for output/adjustment; here: adoption, adoptingoutput/adjustment; here: adoption, adopting

in original formulation: does the in original formulation: does the immigrant want to establish relationships immigrant want to establish relationships with new culture? with new culture?

Problem: Narrow conceptualizationProblem: Narrow conceptualization102102

Cultural maintenanceCultural maintenance• maintaining characteristics of own maintaining characteristics of own

(heritage) culture (heritage) culture

Cultural adoptionCultural adoption• adopting characteristics of the adopting characteristics of the

culture of the society of settlementculture of the society of settlement

Acculturation ModelsAcculturation Models

Unidimensional modelUnidimensional model

Bidimensional modelBidimensional model

Cultural Cultural Cultural Cultural maintenancemaintenance adoptionadoption

Cultural maintenanceCultural maintenance

Cultural adoptionCultural adoption

YesYes

Cultural adoption?Cultural adoption?

CulturalCultural

maintenancmaintenance?e?

Berry’s Bidimensional ModelBerry’s Bidimensional Model

NoNo

NoNo

YesYes SeparationSeparation IntegrationIntegration

AssimilationAssimilationMarginalizationMarginalization

FeaturesFeatures Correlations of dimensions often varyCorrelations of dimensions often vary

• Conceptually independentConceptually independent• Empirically often negatively relatedEmpirically often negatively related

Dimensions or orientations more important?Dimensions or orientations more important?• Methodologically: dimensions often easier to deal Methodologically: dimensions often easier to deal

withwith• Conceptually: orientations prevailConceptually: orientations prevail

Note that integration refers to biculturalism Note that integration refers to biculturalism in psychology and to sociocultural outcomes in psychology and to sociocultural outcomes in sociology (a well integrated immigrant is a in sociology (a well integrated immigrant is a person who speaks the mainstream language, person who speaks the mainstream language, has a paid job, etc.)has a paid job, etc.)

Fusion ModelFusion Model

Cultural adoptionCultural adoption

CulturalCultural

maintenance maintenance

New New

cultureculture

•Conceptually domains independentConceptually domains independent•Empirically not always the caseEmpirically not always the case

•Will depend on a host of factors, such as Will depend on a host of factors, such as cultural distance, perceived pressure to cultural distance, perceived pressure to assimilate, …assimilate, …•Often slightly negative correlationsOften slightly negative correlations

•Example: we found a clear negative corelation in Example: we found a clear negative corelation in the evaluations of Dutch and Turkish culture in a the evaluations of Dutch and Turkish culture in a group of Turkish-Dutchgroup of Turkish-Dutch

Domain SpecificityDomain Specificity

•Acculturation variables Acculturation variables (conditions, (conditions, orientations, and outcomes) orientations, and outcomes) are mixed are mixed •Reliance on ‘Proxy’ measures of Reliance on ‘Proxy’ measures of acculturation, such as length of stay acculturation, such as length of stay (poor validity)(poor validity)

•Reliance on single-index measures Reliance on single-index measures (do (do not fully account for construct)not fully account for construct)

Assessment of Acculturation:Assessment of Acculturation:Recurrent ProblemsRecurrent Problems

Assessment of Acculturation:Assessment of Acculturation:Recurrent Problems (cont’d)Recurrent Problems (cont’d)

Measure of only adoption dimension, not of Measure of only adoption dimension, not of maintenance dimensionmaintenance dimension

Acculturation aspects (e.g., cognition, Acculturation aspects (e.g., cognition, values, attitudes) are often combined. values, attitudes) are often combined. • Sound and meaningful?Sound and meaningful?

No psychometric properties reportedNo psychometric properties reported Often emphasis on actual behavior and Often emphasis on actual behavior and

language proficiencylanguage proficiency• Measures often assess sociocultural Measures often assess sociocultural

outcomes that are used to predict other outcomes that are used to predict other outcomes (e.g., school performance)outcomes (e.g., school performance)

Measure of only adoption dimension, not of Measure of only adoption dimension, not of maintenance dimensionmaintenance dimension

OutcomesOutcomes

Focus on two kinds of outcomesFocus on two kinds of outcomes• Psychological adjustment (stress & coping)Psychological adjustment (stress & coping)• Sociocultural adjustment (social learning)Sociocultural adjustment (social learning)

Almost no studies of cultural maintenanceAlmost no studies of cultural maintenance• This lack of balance absent in This lack of balance absent in

sociolinguistics where both acquisition of sociolinguistics where both acquisition of mainstream and loss of ethnic languages is mainstream and loss of ethnic languages is studiedstudied

• This lack of balance is also absent in study This lack of balance is also absent in study of acculturation orientationsof acculturation orientations

Measurement Methods Measurement Methods

Bidimensional model:Bidimensional model:

(2) Two-statement method (2) Two-statement method

(maintenance; adoption)(maintenance; adoption)

(3) Four-statement method (3) Four-statement method

(acculturation strategies)(acculturation strategies)

Unidimensional model:Unidimensional model:

(1) (1) One-statement method One-statement method (more - less)(more - less)

(1) One-Statement Method(1) One-Statement Method

Example item (1 statement for 1 domain) Example item (1 statement for 1 domain) only Turkish friends.only Turkish friends.

more more

Turkish than Dutch friends. Turkish than Dutch friends. I find it important to have I find it important to have as many as many Turkish as Dutch friends.Turkish as Dutch friends. more Dutch than more Dutch than Turkish friends.Turkish friends. only Dutch friends. only Dutch friends.

no Dutch and no Turkish no Dutch and no Turkish friends.friends.

AdvantagesAdvantages

Short(est) questionnaire Short(est) questionnaire

• ProblemProblem

One dimension?One dimension?

HeritageHeritage MainstreamMainstream

RecommendationRecommendation

This method is often quite useful This method is often quite useful in practice, despite conceptual problemsin practice, despite conceptual problems

Take domains into considerationTake domains into consideration

publicpublic DutchDutchprivateprivateTurkishTurkish

Research findingsResearch findings

Domain specificity (public, private Domain specificity (public, private components) components)

(1) One-Statement Method(1) One-Statement Method

115115

(2) Two-Statement Method(2) Two-Statement Method

Example (domain friends)Example (domain friends) I think it is important to have Dutch friends. 1 2 3 4 5 6 7I think it is important to have Dutch friends. 1 2 3 4 5 6 7

I think it is important to have Turkish friends. 1 2 3 4 5 6 7I think it is important to have Turkish friends. 1 2 3 4 5 6 7

Disadvantages/questionsDisadvantages/questions Are the two dimensions really independent? Are the two dimensions really independent?

How to define the four acculturation orientations?How to define the four acculturation orientations?

AdvantagesAdvantages

The two dimensions are measured independentlyThe two dimensions are measured independently

Items are not complexItems are not complex

Questionnaire is still shortQuestionnaire is still short

How to Define the Four Acculturation How to Define the Four Acculturation Orientations?Orientations?

Sample-dependent coding:Sample-dependent coding:

• Mean or (more common) median splitMean or (more common) median split

Advantage: optimal spread of participants Advantage: optimal spread of participants

across orientationsacross orientations

Disadvantage: validity can be problematic in Disadvantage: validity can be problematic in

groups with a shared preference (often the groups with a shared preference (often the

case for integration)case for integration)

How to Define the Four Acculturation How to Define the Four Acculturation Orientations? (cont’d)Orientations? (cont’d)

• Response scale-dependent codingResponse scale-dependent coding

– Midpoint split (average scores above or Midpoint split (average scores above or

below midpoint of scale)below midpoint of scale)

• Advantage: face validityAdvantage: face validity

• Disadvantage: what to do when scale has even Disadvantage: what to do when scale has even

number of anchors? Solutions such as random number of anchors? Solutions such as random

split or allocating these to a single group have split or allocating these to a single group have

an unavoidable arbitrarinessan unavoidable arbitrariness

(2) Two-Statement Method(2) Two-Statement Method ResultsResults

• Possible method factor, e.g., all maintenance items Possible method factor, e.g., all maintenance items

togethertogether

• Domain dependence:Domain dependence:

public domain (Tu, Du) public domain (Tu, Du)

private Dutch domain private Dutch domain

private Turkish domain private Turkish domain

• Domain dependence does not always show up as Domain dependence does not always show up as

separate factors (usually based on differences in mean separate factors (usually based on differences in mean

scores)scores)

Potential problem:Potential problem:

• Two scores are sometimes converted to Two scores are sometimes converted to

four orientations (e.g., distance method), four orientations (e.g., distance method),

which introduces dependencies in the datawhich introduces dependencies in the data

RecommendationRecommendation

This method can be used This method can be used

Take domains into considerationTake domains into consideration

7

6

5

4

3

2

1

(1,7)Separation

(7,7)Integration

Marginalization(1,1)

Assimilation(7,1)

Cultural adoption (Du)

Culturalmaintenance

(Tu)

1 2 3 4 5 6 7

Acculturation Strategies

PrivatePublic

Results of the ‘one-statement’ and the Results of the ‘one-statement’ and the ‘two-statement’ measurement methods: ‘two-statement’ measurement methods: domain specificitydomain specificity

(1,7)Separation

(7,7)Integration

Marginalization(1,1)

Assimilation(7,1)

PrivatePrivate PublicPublic

77

66

55

44

33

22

11

Cultural adoption (Dutch)Cultural adoption (Dutch)

CulturalCultural

maintenancmaintenancee

(Turkish)(Turkish)

1 2 3 4 5 6 71 2 3 4 5 6 7

PublicPublic DutchDutchPrivate Private

TurkishTurkish

Summary of ResultsSummary of Results

(3) Four-Statement Method(3) Four-Statement Method

Example item (4 items for 1 domain) Example item (4 items for 1 domain) (Int)(Int) I find it important to have Dutch friends and 1 2 3 4 5 I find it important to have Dutch friends and 1 2 3 4 5

I find it also important to have Turkish I find it also important to have Turkish friends. friends.

(Sep)(Sep) I find it not important to have Dutch friends 1 2 3 4 5 I find it not important to have Dutch friends 1 2 3 4 5 but I find it important to have Turkish but I find it important to have Turkish friends. friends. AdvantageAdvantage

The four strategies are measured independentlyThe four strategies are measured independently

Disadvantages (questions)Disadvantages (questions)

Complex items (see Marginalization)Complex items (see Marginalization)

Questionnaire is long (per domain 4 questions)Questionnaire is long (per domain 4 questions)

Factors and (independent) dimensions?Factors and (independent) dimensions?

Research findingsResearch findings

Bipolar unidimensional structureBipolar unidimensional structure

(-) Integration(-) Integration (+) A S M(+) A S M

80-85% of our immigrant Dutch samples 80-85% of our immigrant Dutch samples prefer integration (one score) prefer integration (one score)

AdvantagesAdvantages

Method is broad Method is broad

Measure integration with more detailsMeasure integration with more details

(3) Four-Statement Method(3) Four-Statement Method

Summary of ResultsSummary of Results

MeasurementMeasurement Results Results methods methods

Four-statement Four-statement Insufficient discrimination: Insufficient discrimination: integration vs not-integrationintegration vs not-integration

One-statementOne-statement Discrimination between public Discrimination between public and private domainsand private domains

Two-statementTwo-statement More detailed information within More detailed information within domainsdomainsTwo-statement method often works Two-statement method often works

best.best.

Questions to consider when Questions to consider when choosing/designing an instrumentchoosing/designing an instrument

1. 1. The clear formulation of research goals The clear formulation of research goals and choice of acculturation variables.and choice of acculturation variables. What is the role of acculturation in the What is the role of acculturation in the

study? Antecedent, study? Antecedent, mediating/moderating, or outcome mediating/moderating, or outcome variablevariable

2. Which acculturation aspects are dealt 2. Which acculturation aspects are dealt with?with?

• knowledge, values, attitudes, or knowledge, values, attitudes, or behaviorbehavior

3. The choice of research methodology 3. The choice of research methodology (how to study?)(how to study?)

• ““Soft” or “hard” measuresSoft” or “hard” measures• Self-reports, observations, …Self-reports, observations, …

4. The choice of a measurement method 4. The choice of a measurement method (how to assess acculturation?)(how to assess acculturation?)

• Orientations: one-, two-, and four-Orientations: one-, two-, and four-statement methodstatement method

• Perceived or actual environmental Perceived or actual environmental conditionsconditions

Multilevel issues may be involved Multilevel issues may be involved when both individual and contextual when both individual and contextual variables are consideredvariables are considered

5. The choice of life domains and 5. The choice of life domains and situations to be dealt with in the itemssituations to be dealt with in the items

in which domains and situation to in which domains and situation to assess?assess?

6. Choice of item wording. 6. Choice of item wording. • Questionnaires often in second Questionnaires often in second

languagelanguage• Use simple languageUse simple language

An Empirical StudyAn Empirical Study

Methods (dMethods (dimensions) of acculturationimensions) of acculturation

(1) One-statement method(1) One-statement method

(2) Two-statement method(2) Two-statement method

(3) Four-statement method(3) Four-statement method

Domain(s) of aDomain(s) of acculturation cculturation

Private domains Private domains (celebrations, child-rearing)(celebrations, child-rearing)

Public domains Public domains (language, education, living)(language, education, living)

ParticipantsParticipants 293 Turkish-Dutch adolescents 293 Turkish-Dutch adolescents

Gender: 144 female and 149 maleGender: 144 female and 149 male

Generation: 15 first and 278 second generationsGeneration: 15 first and 278 second generations

Age: 11 - 19 years, M = 14.67 Age: 11 - 19 years, M = 14.67 (SD = 1.69)(SD = 1.69)

Education: Secondary SchoolEducation: Secondary School

Instrument and procedureInstrument and procedure (1) 15 items on 15 domains (7 private and 8 public) (1) 15 items on 15 domains (7 private and 8 public)

(2) 30 items on 15 domains (7 private and 8 public) (2) 30 items on 15 domains (7 private and 8 public)

(3) 36 items on 9 domains (5 private and 4 public)(3) 36 items on 9 domains (5 private and 4 public)

Public

domain

Private

domain

.88$

.75##

Two-item methodTurkish culturePublic domain

Two-item methodTurkish culturePrivate domain

One-item methodPrivate domain

One-item methodPublic domain

Two-item methodDutch culturePublic domain

Two-item methodDutch culturePrivate domain

Four-item methodSeparartionPublic domain

Four-item methodIntegrationPrivate domain

Four-item methodSeparationPrivate domain

Four-item methodIntegrationPublic domain

One-itemmeasurementmethod

Two-itemmeasurementmethod

Four-itemmeasurementmethod

.12#

.65#

.96$

.26#

.48$

.24

.68

.43

.67$

.89$

.31

-.32

-.06#

-.88$ .67

-.85

-.70

.69

.54

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-.81

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E

A

S

U

R

E

M

E

N

T

A

C

C

U

L

T

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R

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I

O

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134134

Summary of ResultsSummary of Results

Measurement methods of acculturationMeasurement methods of acculturation

One- and two-statement methods: no One- and two-statement methods: no significant influences of measurementsignificant influences of measurement on outcome on outcome

Four-statement method: the largest Four-statement method: the largest influence on outcomeinfluence on outcome

Domain specificity Domain specificity

Distinct but interrelated positive relationship Distinct but interrelated positive relationship between private and public domainsbetween private and public domains