On the basis of Schafer's multiple imputation program, I have computed five data "complete" sets from a sample of 790 cases, and in turn have tested a structural equation model with each data set. (You may be wondering why I did not use the FIML option for estimating SEM models with missing data, that is available in a number of programs. The problem is that I have a dichotomous endogenous variable [mortality] that will not work with the missing data options currently available in these programs.) I now have five chi-square values reflecting the fit of the model to each data set. My question is, how should one combine these chi-square values across data sets to get an "average" value, that reflects the fit of the model across data sets? I believe there may be some work by Rubin and his colleagues on this issue; any references that anyone could provide me with to this or other relevant literature would be greatly appreciated.
Thanks, Dan Daniel W. Russell Professor, Department of Psychology and Institute for Social and Behavioral Research Iowa State University 2625 N. Loop Drive, Suite 500 Ames, IA 50010-8296 USA (515) 294-7081 Fax: (515) 294-3613 Homepage: http://psych-server.iastate.edu/faculty/drussell/homepage.htm
