Hello, I have a clustered longitudinal dataset consisting of four waves of data on individuals who are nested in neighborhoods. I have missing data on several time-varying variables at both the individual- and neighborhood-levels. There are also some time-invariant individual variables. From what I gather in the documentation, I should do the following things to account for this data structure: -make sure the data is structured in long format, with a time indicator and 4 rows for each individual. -identify time series variable with ts = ____ option -identify individual ID with idvars = ____ option -identify neighborhood ID with cs = ____ option -use to intercs = TRUE option to allow variation time trends Here are my questions: 1. Am I specifying the cross section variable properly? Do I really have two cross section variables (individual ID and neighborhood ID) or does the idvars and ts options account for the clustering within person, over time? 2. How do I tell Amelia that some variables are time varying and some are time invariant? Is there a way to have polytime=0 for some variables to force a constant time trend, but then have polytime=1 for others? Thanks, -WRJ -- William Johnston Doctoral Candidate Harvard Graduate School of Education -- Amelia mailing list served by HUIT [Un]Subscribe/View Archive: http://lists.gking.harvard.edu/?info=amelia More info about Amelia: http://gking.harvard.edu/amelia Amelia mailing list Amelia(a)lists.gking.harvard.edu To unsubscribe from this list or get other information: https://lists.gking.harvard.edu/mailman/listinfo/amelia