RE: An approach for imputing missing independent variable (covariate)

From: "Gibiansky, Leonid" <gibianskyl@globomax.com> Subject: RE: An approach for imputing missing independent variable (covariate) Date: Wed, 20 Sep 2000 09:41:19 -0400 Vladimir, Essentially, you allow your covariate to "float" so that the imputed missing value would not "disturb" your model. My impression is that it is the same as use NEWCOV instead of COV where NEWCOV = COV (if COV is not missing) NEWCOV = THETA(10)+ETA(10) $THETA ... 0 ; or any reasonable initial value and range $OMEGA .... HUGE FIXED; to allow any value that is convenient for the model Is there any difference with your approach ? POSTHOC value for NEWCOV should be equal to the result of your iteration scheme. Alternatively, you may first model the covariate distribution independently (approximate it by the normal distribution, if possible, and find mean and variance), and then fix thata(10) and omega(10) at those values. In this case, you place some restrictions on the missing covariate value by using distribution of the not-missing covariate values. Leonid