Use of Survival Data in Multivariate Adaptive Regression Analysis: Simulation Study
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Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Objective: The multivariate adaptive regression splines (MARS) is very effective in order to model linear or non- linear relationships. The Cox regression residuals-based MARS model, which integrates Cox regression and MARS approaches, was created to assess the relationships between efficient risk factors on the survival. The purpose of this study is to introduce the Sur- vival-MARS (SM) model which uses the Cox-Snell, Martingale, and deviance residuals. Also,our aim is to compare the performance of the models created with residuals at different sample sizes and correlation levels with the simulation study in order to determine the most effective residual type that can be used in the SM model. Material and Methods: Performances of SM models that use Cox- Snell,Martingale, and deviance residual types were compared at different sample sizes (n = 30, 100, 150, 250, 500, 1.000), with both no correlation (r = 0.00) and medium (r = 0.50) and high (r = 0.90) correlations between predictors. SM model performances were compared via minimum generalized cross-validation and the sum of mean squared error values.. Results: In all scenarios, SM models with Cox-Snell residuals have the best performance compared to other models established with other residuals. Martingale and devi- ance residuals were affected by high correlation and low sample sizes. Conclusion: In case of linear relationship between risk fac- tors, SM models with Cox-Snell residuals are quite successful in explaining these relationship structures and enable the effects on the dependent variable to easily interpret.
Açıklama
Anahtar Kelimeler
Cox regression, Multivariate adaptive regression splines, Cox-Snell residual, Martingale residual, deviance residual
Kaynak
Türkiye Klinikleri Biyoistatistik Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
15
Sayı
1
