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We used multiple multivariate imputation, using all variables included in any analyses, the censoring indicator and the log of survival time for Cox models, to impute missing values for those variables with some missing data [17].
Covariate data from those missing year 5 weights were then entered into the models to impute the missing weights.
The imputation was done using multiple imputations by chained equations (MICE), an approach that uses all the variables in the models to impute the missing values [ 25].
All exposures, outcomes, covariates, and predictors of missingness were included in prediction models to impute data, except for TBLH and spine ABMC because these were derived from TBLH and spine BMC and BA.
First, it exemplifies the use of tree models to impute unordered marker data in GWAS and, in the context of multivariate MI, approximate the distribution p (X ^ mis | X obs ) by following the methodologies developed by Dai et al. (2006) and Burgette and Reiter (2010).
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Shafer (2001) used this imputation model to impute the NHANES III dataset after modeling nonnormally distributed variables.
I apply an engineering thermal load model to impute balance point temperatures for residential households in the Puget Sound Energy Washington service territory.
Beagle uses population information and a hidden Markov model to impute missing genotypes.
This suggests the possibility of population sub-sampling and use of modeling to impute values for endotoxin.
We attempted to overcome this limitation by using a prediction model to impute the missing cadmium data (Tellez-Plaza et al. 2010).
30 As ethnicity could be predicted from the other variables in the complete data, we were able to use a plausible model to impute the missing values.
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