There are three major considerations when doing a power analysis for sample size determination, and our statisticians will consider each point carefully while completing your power analysis:
- The general approach to determining sample size assumes that a simple random sample is the sampling design. More complex designs, e.g., stratified random samples, must take into account the variances of subpopulations, strata, or clusters before an estimate of the variability in the population as a whole can be made.
- The sample size should be appropriate for the statistical analysis that is planned. If descriptive statistics are to be used, for example, then any reasonable sample size will suffice. On the other hand, a good size sample, approximately n=150+, is usually needed for multiple regression, analysis of covariance, or log-linear analysis, which might be performed for more rigorous state impact evaluations. In addition, an adjustment in the sample size may be needed to accommodate a comparative analysis of subgroups (such as an evaluation of program participants with nonparticipants). For all of these cases, before conducting a power analysis, you must have identified all necessary tests to analyze your data–and if you are still finalizing your statistical analysis, we can absolutely assist.
- Finally, the sample size formulas provide the number of responses that need to be obtained. Many researchers commonly add 25%+ to the planned sample size to compensate for persons that the researcher must remove from the sample for some reason. The number of surveys or questionnaires also can be substantially larger than the number required, based on the assumed response rate.
