My previous posts discussed the p-values that the base module of SPSS reports for statistical significance tests using weighted data; these weights are not correct for probability-weighted analyses. Jon Peck informed me of SPSS Complex Samples, which can provide correct p-values for statistical significance tests for probability-weighted analyses. Complex Samples does not have the most intuitive setup, so this post describes the procedure for analyzing data using probability weights in SPSS Statistics 21.

The dataset that I was working with had probability weights but no clustering or stratification, so the Stratify By and Clusters boxes remain empty in the image below.

The next dialog box has options for Simple Systematic and Simple Sequential. Either method will work if Proportions are set to 1 in the subsequent dialog box.

I conducted an independent samples t-test, so I selected the General Linear Model command below.

Click the Statistics button in the image above and then click the t-test box in the image below to tell SPSS to conduct a t-test.

Hit OK to get the output.

The SPSS output above has the same p-value as the probability-weighted Stata output below.