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st: Imputing for missing proportions

From   Geomina Turlea <>
Subject   st: Imputing for missing proportions
Date   Thu, 11 Apr 2013 15:21:13 +0100 (BST)

Good afternoon, 
I am fighting for a while with estimate missing data for the share of ICT professionals/total employment, in 59 industries, 27 EU countries and for 14 years. 
This data exists in the European Labour Force Survey, but the dataset is incomplete. 
1. Can I use mi impute with proportions? 
2. I used betafit to fit a distribution with values between 0 and 1. Than I imputed the missing values from the estimated beta distribution. Is this method superior/inferior to using mi impute? 
3. I tried to use the Kolmogorov-Smirnov test, but I don't know what I got wrong. Below is a sequence where I created a variable with the distribution beta and then test the hypothesis with the K-S test. The test rejects the null hypothesis that the data has the distribution I used to create it. How could that be? 
. gen x=rbeta(0.05, 1.77) 
. ksmirnov x=rbeta(0.05, 1.77) 
One-sample Kolmogorov-Smirnov test against theoretical distribution
           rbeta(0.05, 1.77) 
 Smaller group       D       P-value  Corrected
 x:                  1.0000    0.000
 Cumulative:        -0.9381    0.000
 Combined K-S:       1.0000    0.000      0.000
Thank you very much, 

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