SAMPLING TECHNIQUES

Dr. Yinka Adeniran, FMCPHLecturer/Consultant

LEARNING OBJECTIVES

At the end of this lecture, you should be able to:

■Identify and describe the common methods of sampling

■Discuss problems of bias that should be avoided when selecting a sample

■Select the sampling method most appropriate for the research design being developed

SAMPLING■This is the selection of

one or more study units from a defined study population.

Questions that need to be answered:■ What is the group of people (study

population) from which a sample is to be taken?

■ How many people need to be included in the sample?

■ How will these people be selected? An ideal sample should be representative

of the population from which it is drawn, i.e. it should have all the major characteristics of that population

STUDY POPULATION■ The study population should be clearly defined, e.g.

according to age, sex, and residence.■ Each study population consists of study units. A

study population could consist of persons, villages, institutions, records, equipment, etc.

Problem to be studied Study population Study unitImmunisation coverage of children 12-24 months of age in Abakaliki

All children 12-24 months of age in Abakaliki

One child 12-24 months of age in Abakaliki

Environmental sanitation in primary schools of Mushin, Lagos

All primary schools in Mushin

One primary school in Mushin

Participation in the NHIS by private health facilities in Yaba LCDA

All private health facilities in Yaba LCDA

One private health facility in Yaba LCDA

SAMPLING METHODS

1. Probability sampling methods2. Non-probability sampling

methods

Probability sampling methods■Simple random sampling■Systematic sampling■Stratified sampling■Cluster sampling■Multistage sampling

Non-probability sampling methods

■Convenience sampling■Quota sampling

NON-PROBABILITY SAMPLING METHODS■The Sampling Frame is a listing of all

the study units that are contained within the study population

■If a sampling frame is not available, it is not possible to sample the study units in such a way that the probability for the different units to be selected in the sample is known. In such cases, non-probability sampling techniques are used in taking a sample.

Convenience sampling■ For the sake of convenience, the study units

that happen to be available at the time of data collection are selected into the sample.

■ E.g. interview of all youths gathered at a street viewing centre within Ilepa village, to determine the attitude of teenagers in the village towards VCT.– More convenient than taking a random sample of

the teenagers in the village– Gives a useful idea of their views– However, sample may not be representative of

the village teenagers

Quota Sampling■ This is a method that ensures the inclusion of a

certain number of sample units from different categories with specific characteristics in the sample, so that the various characteristics are represented.

■ In this method, the investigator includes as many people in each category of study unit as he can find until that quota is filled. – E.g. inclusion of 20 patients each from different religious

groups in a study on attitudes towards family planning– Useful when a convenience sample may not provide the

desired balance of study units.– However, may still not be representative of the study

population

PROBABILITY SAMPLING METHODS■ These are used to select a sample when the aim

of the research is to measure variables and generalise the findings obtained to the total study population.

■ They involve random selection procedures that ensure that each unit of the sample is selected on the basis of chance. All units of the population should have an equal or a known chance of being included in the sample.

■ Probability sampling methods require a listing of all the study units within the population to be studied. This list is referred to as the sampling frame.

Simple Random Sampling■ The simplest form of probability samplingSteps:■ Make a numbered list of all the units in the

population from which the sample is to be drawn■ Decide on the size of the sample■ Select the required number of sampling units

through one of the following methods:– Balloting– Use of table of random numbers

■ E.g. a simple random sample of 50 primary school students from a school population of 250

Systematic sampling

■ Study units are chosen at regular intervals from the sampling frame.

■ The interval that is chosen for selection is called the sampling interval.

■ The number of the first study unit to be chosen is selected through simple random sampling, and then the sampling interval is applied.

■ Sampling fraction = sample size/study population– In the last example, that would be 50/250 =

1/5– The sampling interval would therefore be 5

Systematic sampling (II)

Advantages:■ Less time-consuming & easier to carry out

than simple random sampling.

Disadvantages:■ Risk of bias – sampling interval may

coincide with a systematic variation in the study population

STRATIFIED SAMPLING■ If it is important that the sample includes representation

from various groups of study units with specific characteristics, e.g. residents from rural and urban areas, different classes in a school, then the sampling frame must be divided into groups, or strata, according to these characteristics.

■ Samples of a predetermined size are obtained from each stratum within the study population using another probability sampling method.

■ Stratified sampling is only possible when the proportions or size of each strata that make up the study population are known.

■ The sampling fraction for each of the strata could be the same, i.e. proportionate, or could differ for each strata, i.e. non-proportionate.

Stratified sampling (II)

Advantages:■ Representation of various sub-groups or strata

of interest within the study population

Disadvantages:■ Unequal sampling fractions may give a

different picture of the situation found from research, when generalising to the study population.

Cluster Sampling■ This is the selection of groups of study units

(clusters) instead of individual study units.■ It is used:

– When a complete sampling frame does not exist

– Sampling units are scattered in groups across a very large area

– The list of groupings of study units can be easily compiled, e.g. villages, communities, schools

■ Clusters are often geographic units, e.g. villages, communities, or organizational units, e.g. schools, clinics

Multistage sampling

■ A multistage sampling procedure is carried out in stages or phases, and usually involves more than one sampling method.

■ It is used for community-based studies, usually involving large and diverse populations.

Advantages & disadvantages of cluster and multistage sampling methodsAdvantages:■ Less time-consuming & easier to carry out than

simple random sampling■ A complete sampling frame for each study unit

may not be required

Disadvantages:■ A larger probability that the sample will not be

representative of the total study population than in simple random sampling

BIAS IN SAMPLING Bias in sampling is a systematic error in

the sampling procedure that leads to a distortion in the results of the study

■ This is as a result of improper sampling procedures that result in the sample not being representative of the study population

■ If probability sampling methods are properly employed, then an important source of bias is non-response.

■ Non response may be due to absence of subjects, or from refusal to respond or cooperate with the interviewer.

■ To reduce the effect of non-response, additional people may be included in the sample during selection

■ It is important in any study to mention the non-response rate, and to discuss how it might have affected the results.

Sources of bias in sampling■Non-response■Use of volunteers & other non-

probability sampling techniques■Seasonal bias■Selection of easily accessible areas

as opposed to relatively inaccessible ones