Chapter 4 Research Participants: Samples

Topics of Discussions Sampling: Definition and Purpose –Definition of a population Selecting a Random Sample –Simple Random Sampling –Stratified Sampling –Cluster Sampling –Systematic Sampling

Topics of Discussion (contd) Determining Sample Size Avoiding Sampling Error and Bias Selecting a nonrandom sample Sampling in Qualitative research

Sampling: Definition and Purpose Sampling—a process of selecting a number of individuals for a study in a way that represents the larger group from which they were selected. A sample represents the larger group—population Purpose of sampling—to gain information about the population by using the sample Generalizability—the degree to which the results of the sample maybe applicable to the entire population and situations. Target population—population to which the researcher wants to generalize the results to. Accessible population?

Selecting a Random Sample A good sample is one that is representative of the population from which it was selected Sampling techniques: –Random sampling—all individuals in the defined population have an equal and independent chance of being selected for the sample –Stratified Sampling—selection of a sample in ways where the identified subgroups are represented as in the target population. (104) eg. If population is 30% minority, sample should contain 30% minorities etc.

Cluster Sampling –Cluster sampling randomly selects groups, not individuals. –All members of selected groups have similar characteristics. –(Steps in cluster sampling—130) –Drawbacks—chances are greater of selecting a sample that is not representative of population.

Systematic Sampling Not used often—sampling in which individuals are selected from a list by taking every Kth name. K=population/sample size Random Sampling Strategies table - important to know—the advantages and disadvantages.

Determining Sample Size Rule of Thumb—sample should be large enough to be generalizable to the entire population otherwise you cannot claim generalizability. 30 participants minimum recommended The larger the population, the smaller the percentage of population required. See Table 4.2:sample sizes Vs Populations

Sampling Error and Bias Sampling error—beyond the control of the researcher—reality of random sampling Sampling bias-it is nonrandom and a fault of the researcher. EX: Sampling bias affects the validity of the study

Non-Random Samples Or Non-probability sampling—sampling methods that do not have random sampling at any stage of sample selection –Convenience sampling—includes whoever is available –Purposive sampling—judgement sampling— used often for qualitative studies –Quota sampling

Sampling in Qualitative Research Purposive Sampling used. –Intensity sampling—permits study of different levels of the research topic within one group (diversity-good students, poor students etc) –Homogenous sampling-no diversity. Sample has similar characteristics –Snowball sampling—selecting few participants who identify other good participants –Random purposive sampling—selecting randomly from a purposive sample

Qualitative Sampling –Qualitative research uses sampling strategies that produce samples that are predominantly small and non random. –Keeps in line with QR’s emphasis on in-depth description of participants’ perspectives and context. –Purposive sampling ensures that the “best” participants are included.

Task 4: Choosing your sample Define the population (size, relevant characteristics—age, ability, socioeconomic status Procedural technique for selecting sample- what sampling techniques will you use (eg. Stratified-and how and why). How will the sample be treated or be assigned to groups?