Dear list members,
I am working with a set of survey data (n is about 1000) which
contains 36 items with missing values (min 0.1% missing, up to 16%
max). The items are surveyed on a seven point scale, so they are,
strictly speaking, on a categorical measurement level.
I have only a little theoretical knowledge on imputation techniques,
but virtually no practical experience. What I would like to do in
Stata is something like a multiple imputation using EM while
considering the items metric. Or I would like to use some logistic /
probit link function in a mulinomial model to impute categorical
variables directly.
I have read a bit about -ice- and -uvis-, whith the latter I
understand that I can impute using -mlogit-, the earlier using
"multiple imputation by chained equations", which I do not know of.
Should I use one of these or is there any other good procedure? Can
anybody recommend / advise me on a good imputation procedure for my
case?
Best regards and thanks for reading
Thomas
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