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| From | Maarten Buis <maartenlbuis@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: Imputing for missing proportions |
| Date | Thu, 11 Apr 2013 17:28:58 +0200 |
On Thu, Apr 11, 2013 at 4:21 PM, Geomina Turlea wrote: > 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) My first step would be to look at the industries with missing values. Sometimes missing just means 0 or negligable, and looking at the industries would give you a fair guess of whether that is the case. If that is the case your imputation problem reduces to just a recoding problem. For questions 2 and 3: If you have an imputation problem, then you should use -mi- and not -betafit- (available from SSC), because that is what -mi- was designed for. For question 3: -rbeta()- gives you random numbers from a beta distribution, so that is definately not something you want to feed in -ksmirnov-. I just would use either -margdistfit- or -hangroot- (also available from SSC) after -betafit- to check the fit. -- Maarten --------------------------------- Maarten L. Buis WZB Reichpietschufer 50 10785 Berlin Germany http://www.maartenbuis.nl --------------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/