Sampling in qualitative research

Sampling in quantitative studies Type: Random selectionPurpose: To avoid systematic biases in the sample. The sample size is decisive for generalization. 1. Random sampleTo achieve a representative sample that allows for generalization for the entire population. 2. Stratified sampleTo generalize for specially selected subgroups within the population

Strategic selection in Case Studies Purpose: to maximize the utility of information from small samples and single cases. Select cases on the basis of your expectations about what the cases can tell you. Extreme/deviant casesFor information on unusual cases, which can be especially ‘problematic’ or especially ‘good’ Maximum variation casesFor information on the significance of specific circumstances for processes and outcomes Critical casesFor information permitting logical deductions like, “If this is valid for this case, then it applies to all cases.”

Examples of selection types and purposes Selection of sites/region for intensive study Selection of households/individuals for collecting contextual information Selection of individuals/households/couples or father-son, mother-daughter pairs for purposive inquiry

Examples of extreme/deviant case strategic sampling 1.If only a few schools are producing excellent results, study them to see how they do it 2.If you are interested in truancy problems in particular kinds of schools, study the ones with the lowest and highest rates

Examples of maximum variation strategic sampling 1. If you think school results are affected by ethnic group, choose some schools with no members of that group, some with a few members, some with a balance between two or three groups, and some dominated by that group.

Examples of critical case sampling 1.If you want to test whether X (better health) is caused by Y (good schooling experiences) then select people who have most schooling and those with least schooling to maximise the chances of being able to see whether (and if so, how) schooling makes a difference. 2.In general, if you want to test a theory you think is wrong, choose the case where it is most likely to be true and see if it is (or why it is); don’t choose cases where the conditions are unlikely to produce the predicted outcome