Clustering and multiple imputation of missing data
نویسندگان
چکیده
منابع مشابه
Multiple Imputation for Missing Data
Multiple imputation provides a useful strategy for dealing with data sets with missing values. Instead of filling in a single value for each missing value, Rubin’s (1987) multiple imputation procedure replaces each missing value with a set of plausible values that represent the uncertainty about the right value to impute. These multiply imputed data sets are then analyzed by using standard proc...
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background: prognostic models have clinical appeal to aid therapeutic decision making. two main practical challenges in development of such models are assessment of validity of models and imputation of missing data. in this study, importance of imputation of missing data and application of bootstrap technique in development, simplification, and assessment of internal validity of a prognostic mo...
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ژورنال
عنوان ژورنال: International Journal of Basic and Applied Sciences
سال: 2015
ISSN: 2227-5053
DOI: 10.14419/ijbas.v5i1.5470