Auxiliary Variables Predicting Missing Data
نویسندگان
چکیده
منابع مشابه
Running head: SELECTION OF AUXILIARY VARIABLES 1 Selection of auxiliary variables in missing data problems: Not all auxiliary variables are created equal
The treatment of missing data in the social sciences has changed tremendously during the last decade. Modern missing data techniques such as multiple imputation and full-information maximum likelihood are used much more frequently. These methods assume that data are missing at random. One very common approach to increase the likelihood that missing at random is achieved, consists of including m...
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تاریخ انتشار 2008