Appropriate way to use post-stratification weights when running statistical tests SPSS

Question

I have used Complex Samples in SPSS (and SUDAAN in SAS, Survey in R) when working with survey data that were collected using a sampling design that was not random. For example, when an oversample was included in the data collection. Complex Samples incorporates the sample design into statistical tests, providing more accurate estimates and standard errors.

I am now working with data that were collected from a survey panel and includes post-stratification weights to balance the sample with the population on gender, age, race/ethnicity, region, and education. The weights are not being used to scale estimates to reflect the actual size of the population.

Since this is not a design weight, I am wondering how to apply weights when running a statistical test. Is it sufficient to simply "weight cases" and perform standard statistical tests, or should I treat the post-stratification weights the same way I would treat stratification weights if I had oversampled in the design?

Very much appreciate any assistance.

Answer 1

You should treat the post-stratification weights the same way you would treat stratification weights if you had oversampled in the design? It's not exactly right, but nothing with missing data ever is, and it is quite literally good enough for government work (based on analysis advice for public-use data from post-stratified/raked surveys).