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I don’t know the correct way of modeling as far as imputation model, but I analyze similar data, and one issue that arose was whether to impute the sum of the items or whether to impute the individual items and then sum them up after imputation. We chose the latter. Bill Howells, Wash U, St Louis
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Hi all,
I am working on the large data set on Major depression disorder. One of the outcome variable of interest is the Hamilton Depression Rating Scale(its a17 item scale). About 28% of the exit data are missing. I would like to impute the missing data for the outcome varaible. There are several covariates associated with the outcome of the data among which one variable is highly correlated with the outcome variable. What is the correct way of modeling this kind of data and later for imputation?.
Thanks in advance for any help and suggestion on this question.
Bala University of Pittsburgh
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