Statistics in medicine
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Missing data in public health research is a major problem. Mean or median imputation is frequently used because it is easy to implement. Although multiple imputation has good statistical properties, it is not yet used extensively. ⋯ The simulation showed large differences among various multiple imputation methods with a different number of variables for creating the matching metric for multiple imputation. Multiple imputation using only a few covariates in the matching model produced more biased coefficient estimates than using all available covariates in the matching model. The simulation also showed better standard deviation estimates for multiple imputation than for single mean imputation.
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Statistics in medicine · May 2001
Comparative StudyLogistic regression when binary predictor variables are highly correlated.
Standard logistic regression can produce estimates having large mean square error when predictor variables are multicollinear. Ridge regression and principal components regression can reduce the impact of multicollinearity in ordinary least squares regression. ⋯ Recommendations for choosing among standard, ridge and principal components logistic regression are developed. Published in 2001 by John Wiley & Sons, Ltd.