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Sampling. Basic Terms. Research units – subjects, participants Population of interest (all humans?) Accessible population – those you can actually try to sample Intended sample – those you select for participation Actual sample – those from whom you actually obtain data .

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## Sampling

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**Basic Terms**• Research units – subjects, participants • Population of interest (all humans?) • Accessible population – those you can actually try to sample • Intended sample – those you select for participation • Actual sample – those from whom you actually obtain data**Proximal Similarity Model**• Donald T. Campbell • To whom can you generalize your results? • To the extent that the population is similar to the sample, generalization should be good. • Typical Sample in Psychology is • Students in Introductory Psychology • Laboratory Animals**Simple Random Sampling**• Definition of a random sample • How to obtain one • Sampling frame – a list of all the members of the target accessible population • Each member assigned a random number • Sort by those random numbers • Select n units from the N members • Sampling fraction = n / N • Assumption that sampling fraction = 0**Stratified Random Sampling**• Divide population into strata (nonoverlapping homogeneous subgroups) • Sample nj subjects from each stratum • Proportionate stratified random sampling • Disproportionate stratified random sampling**Proportionate Stratified Random Sampling**• You sample the same proportion from each stratum • For example • 10% of all freshmen at ECU • 10% of all sophomores at ECU • 10% of all juniors at ECU • 10% of all seniors at ECU • 10% of all graduate students at ECU**Disproportionate Stratified Random Sampling**• Some strata have relatively few members • But you want to get a sufficient number of subjects for each stratum • So you sample a larger proportion of those strata with fewer members • For example, nondegree students or doctoral students.**Cluster Random Sampling**• Sampling across a wide geographic region. • Divide the population in clusters – for example, counties in North Carolina. • Randomly sample clusters. • Gather data on all target subjects within each randomly sampled cluster. • For example, all city managers in the selected counties.**Multi-Stage Random Sampling**• Combine two or more techniques • Example • Randomly select 100 classes (clusters) at ECU. • From each class, randomly select 5 students.**Nonrandom Sampling**• Convenience Sampling – get what you can without a lot of hassle • Stand outside of Rawl and try to recruit anybody who comes by • Purposive Sampling – convenience sampling but where you have inclusion/exclusion criteria • For example, subject must be African-American and not live in North Carolina**Nonrandom Sampling**• Modal Instance Sampling – you define the “typical” member of the population and then recruit only such members • ECU: 18 year old female resident of North Carolina • Expert Sampling – recruit only persons who are known to expert in some domain • Designing a survey on social aggression, recruit experts to judge potential survey items.**Nonrandom Sampling**• Proportional Quota Sampling – convenience sampling, except you want subgroups represented in same proportions they are in the target population. • ECU: 30% freshmen, 30% sophomores, 20% juniors, 20% seniors.**Nonrandom Sampling**• Non-proportional Quota Sampling – convenience sampling, except you have specified (nonproportionally) how many subjects you want in each subgroup**Nonrandom Sampling**• Heterogeneity Sampling – you want to have adequate numbers of people in each of two or more groups with disparate opinions. • For example, those who thought the world would end this year, and those who did not • There are a lot fewer of the former, so you would need sample a larger proportion of them.**Nonrandom Sampling**• Snowball Sampling • Identify people who meet your inclusion criteria (for example, lifeguards) • Ask them not only to complete your survey, • But also to send it on to other similar persons they know and ask them to complete it. • Birds of a feather flock together.

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