This question is both about the "survey" package in R and about the mechanics behind it. I'm more interested in the mechanical reasons why this package fails to create weights when combinations of values are missing in the sample.
So my specific problem is this: I have a survey that I would like to post-stratify on age and gender. Since the sampling procedure was difficult, I don't have values for each age-gender combination (gender is coded as binary and age has 5-year brackets). When I use the rake function to post-stratify my sample, I receive the error message
Some strata absent from sample: use partial=TRUE to ignore them. and when I use
partial=TRUE, I receive the error message
unused argument (partial = TRUE). I did some research, and found here that this is the expected behavior. I assume that the program runs into problems when calculating weights for observations that don't occur. Is this assumption correct?
Does this mean that post-stratification isn't possible?
What would be a work-around for such a case?