Longitudinal or cross-sectional weighting with change scores?
I actualy don't think it's quite a change score exactly, but for my outcome variable, I am looking at whether responses to a variable changed between waves 4 and 6. To do this, I created a variable to indicate yes, their answer had changed or no, it had not.
For my predictors, I am using a mixture of wave 4 variables and further "change" variables I have created (or were available in the dataset) to indicate whether there has been change or not between waves 4 and 6.
I have been trying to determine if a longitudinal weight is more appropriate (because I am using variables from more than one wave) or if the wave 6 (or 4), cross-sectional weight would be more appropriate (because I don't have the repeated measures that a more typical longitudinal analysis would). It would be amazing if you are able to advise on this.
I am using some self-completion items and the combined BHPS and UKHLS sample, so I am thinking that my choice in weights comes down to f_indscub_xw or f_indscub_lw, although, please correct me if I'm wrong here.
Sorry if this (or similar) has been answered in previous weighting questions, but I couldn't see anything that quite matched it in the ones I looked through.