Topic | Leader | Status | Most Recent Updated Time |
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Compare MICE, argeimpute, and probably some maximum likelihood methods for normal distribution up to 90% missing |
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Illustration of situations where prediction mean matching may fail,and to develop a diagnostic how a researcher can detect a priori that he/she is in such situation |
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Study the situation when there are multiple covariates and/or outcome missing simultaneously, and check how bad it can get |
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Study categorical missing covariates using Fisher's optimum scoring algorithm, and study how good the prediction mean match based on canonical variable scores is comparing to polytomous logistic full model or MICE |
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Over-fitting (or over-imputing) issue | |||
Compare CC, MICE, and dropping missing variable for diagnostic data there will be one continuous variable, and two binary variables two setting: (a)continous variable is missing (b) one binary variable is missing |
Kristel | working | Nov 27,2006 |