Investigation of the Multiple Imputation Method in Different Missing Ratios and Sample Sizes
| Autor: | B. Barış Alkan, Nesrin Alkan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Complete data
Matematik Computer science Bayesian probability General Engineering Missing data computer.software_genre Missing Value Multiple Imputation Bayesian Cox Regression Data set Bayes' theorem Variable (computer science) Sample size determination Prior probability Data mining computer Mathematics |
| Zdroj: | Volume: 23, Issue: 4 605-609 Sakarya University Journal of Science |
| ISSN: | 2147-835X |
| Popis: | In many studies, missing data are the real trouble to researchers. Because the statistical methods are designed for complete data sets. Multiple imputation method is developed to solve the missing data problem. The method is also used effectively in some useful properties of the Bayes method. If there are missing values in the data set, Bayesian method can be used to prevent the loss of information. In this study, the performance of the multiple imputation method is evaluated by generating survival data with different missing rates and different sample sizes. Also, informative priors and multiple imputation method are used together to prevent the missing information in the variable with missing value. |
| Databáze: | OpenAIRE |
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