ABSTRACT
The previous two applications involved testing covariances and mean differences in a test–retest design with data that were ignorably missing. In the present application, we build on these foundations in order to estimate the power to test differences between groups in longitudinal change under conditions involving both randomly (missing completely at random, MCAR) and systematically (missing at random, MAR) missing data.
