Suppose your data set has pweights but no stratification or clustering. Is there any compelling reason to svyset the data and use svy:, as opposed to just adding [pw = whatever] to each estimation command?
It seems like the latter will let you do a few more things, e.g. lrtest will work with the force option. I am not sure that is a good thing though. I sometimes wonder if [pw=whatever] is too permissive or if svy: is too strict when only pweights are used.
Also, I know that with svy: you are supposed to use the subpop option rather than an if qualifier when analyzing subgroups -- so I assume that would be a reason for using svy: rather than using [pw = whatever].
My own inclination is to svyset and then use svy: just because it is less typing. But, are there stronger arguments, either way, for using one or the other?
I have a feeling this has been asked before (or worse yet, that I have asked it) but I am not finding an answer easily.
It seems like the latter will let you do a few more things, e.g. lrtest will work with the force option. I am not sure that is a good thing though. I sometimes wonder if [pw=whatever] is too permissive or if svy: is too strict when only pweights are used.
Also, I know that with svy: you are supposed to use the subpop option rather than an if qualifier when analyzing subgroups -- so I assume that would be a reason for using svy: rather than using [pw = whatever].
My own inclination is to svyset and then use svy: just because it is less typing. But, are there stronger arguments, either way, for using one or the other?
I have a feeling this has been asked before (or worse yet, that I have asked it) but I am not finding an answer easily.
Comment