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st: Imputing for missing proportions
From
Geomina Turlea <[email protected]>
To
[email protected]
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,
Geomina
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