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st: Multiple Imputation / - uvis- help


From   "Kanter, Rebecca" <rkanter@jhsph.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Multiple Imputation / - uvis- help
Date   Sat, 11 Apr 2009 21:14:26 -0400

Hi,

I am using factor analysis to construct a socio-econonomic status (ses) variable for my dataset (and did so), but noticed that many households are missing (MAR) information on "drainage;" thus I wanted to use multiple imputation methods to impute values for drainage (a non-ordinal categorical variable) so that there wouldn't be thousands of households with a missing ses. I wanted to impute the value based on the values each household has for the other variables used in the factor analysis (i constructed all the categorical variables into binary ones) and thought I could do this MI via uvis, below. At first, I thought I kept getting the below error because some households were missing information on drainage and another variable in this list, so I corrected that by removing them from the uvis (via the draintag==., if draintag==1 then they are missing drainage info and info on another variable listed below); but i still get the same error. If anyone can help me figure out uvis!
  and/or another way to impute the missing drainage values that would be much appreciated. (And just a note, a1-r4 and o1-k4 below are a series of household characteristic binary variables).

. uvis mlogit drainage a1 a2 r1 r2 r3 r4 radio modcon eapp car camioneta vehic tvbw tvcolor refrig gastove othstove washmac boiler comp microwave phone blender vcr ventilador loghexp nfam crowding o1-k4 if draintag==., gen(md2) boot
[imputing by drawing from conditional distribution with bootstrap]
[perfect prediction detected: using augmlogit to impute drainage]
equation 0 not found
r(111);


___________________________________________
Rebecca M. Kanter
PhD Candidate
Johns Hopkins Bloomberg School of Public Health
Department of International Health
Center for Human Nutrition

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