If the test statistic is something like a Wald chi-square (or Hotelling's T), based on point estimates for each group (of something such as the mean) together with the covariance matrix of these point estimates, then you should be able to form an MI covariance matrix combining W+B using the same combining rules as usually used for univariate statisticsm and then use that in calculating the test statistic.
________________________________ From: Impute -- Imputations in Data Analysis [mailto:[email protected]] On Behalf Of David Judkins Sent: Wednesday, November 11, 2009 12:39 PM To: [email protected] Subject: Use of multiple imputations in hypothesis tests other than t-tests I have a dataset with multiple imputations. It is from a five-arm GRT. One arm is a control and the other four are active. I want to test for variation in mean responses across the four active arms. Proc Mixed will give me a test statistic based on each multiple imputation. But how do I combine these? One of colleagues found something in the HLM manual that would suggest that the replicates of test statistics other than t-statistics are averaged with no attention paid to the variability among them. Sound accurate about HLM? Is that the best we can do?
