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st: generating splines in variable with missing data and multiple imputation


From   "Deppen, Steve" <steve.deppen@vanderbilt.edu>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: generating splines in variable with missing data and multiple imputation
Date   Mon, 25 Feb 2013 20:52:48 +0000

I'm using Stata v12 and I have a small (492) dataset with missing data.  One of the variables, pack-years has a non-linear relationship to the outcome of cancer.  Pack-years is best modeled, given my limited degrees of freedom for other variables of interest, as a restricted cubic spline with 3 knots.  I'm missing data within pack years.  I can run:

mkspline pkyr = pack_years, cubic nknots(3)

after I generate my 20 imputed datasets.  However, I believe that my confidence interval may be incorrect.  I know in R, that variance inflation due to imputing the nonlinear variable is maintained using aregImpute and subsequent fit.mult.impute.  I afraid my standard errors are too small since I estimated the splines outside the imputation.  Is there a way to generate splines as a passive variable within the multiple imputation?

Thank you,


Stephen Deppen MA MS
Department of Thoracic Surgery
Institute for Medicine and Public Health
Vanderbilt University Medical Center
(ph) 615-343-6284
(fax) 615 936-3007



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