X hits on this document





8 / 10

When you want a relatively narrow confidence interval (e.g., the estimate that 75% of teachers support a policy plus or minus 4% is more narrow than an estimate of 75% plus or minus 5%).

When you expect a weak relationship or a small effect.

When you use a less efficient technique of random sampling (e.g., cluster sampling is less efficient than proportional stratified sampling).

When you expect to have a low response rate. The response rate is the percentage of people in your sample who agree to be in your study.

Sampling in Qualitative Research

Sampling in qualitative research is usually purposive (see the above discussion of purposive sampling). The primary goal in qualitative research is to select information rich cases.

There are several specific purposive sampling techniques that are used in qualitative research:

Maximum variation sampling (i.e., you select a wide range of cases).

Homogeneous sample selection (i.e., you select a small and homogeneous case or set of cases for intensive study).

Extreme case sampling (i.e., you select cases that represent the extremes on some dimension).

Typical-case sampling (i.e., you select typical or average cases).

Critical-case sampling (i.e., you select cases that are known to be very important).

Negative-case sampling (i.e., you purposively select cases that disconfirm your generalizations, so that you can make sure that you are not just selectively finding cases to support your personal theory).

Opportunistic sampling (i.e., you select useful cases as the opportunity arises).

Mixed purposeful sampling (i.e., you mix the sampling strategies we have discussed into more complex designs tailored to your needs).

Sampling in Mixed Research

Document info
Document views37
Page views38
Page last viewedWed Jan 18 10:47:20 UTC 2017