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Selecting Research Participants
Chapter 6 Selecting Research Participants
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Selecting research participants
In research you select a sample from a population of potential participants. Census – the whole population is researched Inferential statistics – used to make statements (inferences) about the population based on the findings from our sample. Sampling frame – a list of the population from which the sample is drawn.
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Sampling methods Probability Sampling Non-probability Sampling
Techniques for which you can specify the probability that a participant will be selected from a population. Non-probability Sampling It is impossible to specify the probability of selecting any one individual. The sample may or may not be representative of the population.
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Probability sampling Random sampling – a sample is drawn such that each member of the population has an equal probability of being included in the sample. vs. random assignment – requires that participants have been independently assigned to groups.
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Probability sampling Systematic sampling – the population size is divided by your sample size to provide you with a number, k, for example; then from a random starting point you select every kth individual. Stratified sampling – the population is divided into strata based on some population characteristic and participants are randomly selected from each stratum (therefore each stratum is proportionally represented in the sample).
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Probability sampling Cluster sampling – can be used when a population list is not available and researchers simply identify a number of clusters or groups and include all participants in the cluster/group in the sample. Multistage sampling – a cluster technique where smaller clusters are randomly selected from larger clusters that were randomly selected previously.
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Non-probability sampling
Convenience sampling – using whatever participants are easily available. Quota sampling – convenience sampling in which the goal is to select participants with particular characteristics until you have enough. Referral sampling – involves including participants in the sample who have been referred by other participants.
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Sample and effect size Sample size depends on:
the power of the statistic your research design (how many conditions you have) size of the effect variability of the data
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Power revisited You can increase power by increasing the number of participants in your sample. When deciding which sampling method to use consider: How much time do I have? How much money do I have? How much help can I get?
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Describing Your Participants
How many? How Selected? Where do they come from? What age? max & min, mean and s.d Composition Gender breakdown Ethnicity Other important characteristic related to hypotheses Inclusions/Exclusion Compensation
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