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Dergiler / Sakarya University Journal of Science / 2026 / Volume: 23 Issue: 4

Investigation of the Multiple Imputation Method in Different Missing Ratios and Sample Sizes

Nesrin Alkan(Sinop University)0000-0003-1452-4780
B. Baris Alkan(AKDENIZ UNIVERSITY)0000-0002-5851-7833
Sayfa
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Yayın Tarihi
2019-08-01
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Also, informative priors and multiple imputation method are used together to prevent the missing information in the variable with missing value.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In many studies, missing data are the real trouble to researchers.
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Temel Bulgular & Veri:In this study, the performance of the multiple imputation method is evaluated by generating survival data with different missing rates and different sample sizes.
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Sonuç & Katkı:Also, informative priors and multiple imputation method are used together to prevent the missing information in the variable with missing value.
🔬Tür:Research Article
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Missing Value · Multiple Imputation · Bayesian Cox Regression

Abstract

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.

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Bu Makaleye Atıf Yap

Alkan, N., Alkan, B. B. (2019). Investigation of the Multiple Imputation Method in Different Missing Ratios and Sample Sizes. Sakarya University Journal of Science, Volume: 23 Issue: 4. https://doi.org/10.16984/saufenbilder.507450

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Kaynakça (11)

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  2. Cox, D. R. (1972). Regression models and life tables. Journal of the Royal Statistical Society 34:187–220.
  3. Alkan, N. (2017). Assessing Convergence Diagnostic Tests for Bayesian Cox Regression, Communication in Statistics-Simulation and Computation, Vol.46, No.4, 3201-3212.
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  10. Abreu, C. M., Chatkin, J. M., Fritscher, C. C., Wagner, M. B., Pinto, J. A. L. F. (2003). Long-term survival in lung cancer after surgical treatment: is gender a prognostic factor? (http://www.scielo.br/pdf/jbpneu/v30n1/en_v30n1a03.pdf. 26.06.2018)
  11. Alkan, N., Terzi, Y., Cengiz, M. A., Alkan B B. (2013). Comparison of Missing Data Analysis Methods in Cox Proportional Hazard Models. Turkiye Klinikleri Journal of Biostatistic, 5(2), 49-54.