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st: generating splines in variable with missing data and multiple imputation
From
"Deppen, Steve" <[email protected]>
To
"'[email protected]'" <[email protected]>
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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