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Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data
Abstract
Purpose: Survival analysis is a statistical method used in many fields, especially in the field of health. It involves modeling the relationship between the survival time of individuals after a treatment or procedure and the event called response. The presence of outliers in the data may cause biased parameter estimations of the established models. Also, this situation causes the proportional hazards assumption to be violated especially in Cox regression analysis. Outlier(s) are identified with the help of residuals, Bootstrap Hypothesis test and Rank product test.
Method: In R.4.0.3 software, outlier(s) are determined on a clinical dataset by the Schoenfeld residual, Martingale residual, Deviance residual method and Bootstrap Hypothesis test (BHT) based on Concordance index, and Rank product test.
Results: After the cox regression established by the backward stepwise and robust cox regression, it was observed that the established models did not fit. So, the outlier(s) determined by the methods mentioned.
Conclusion: It was decided that only one observation could be excluded from the study. As in the survival data, in many data types, outliers can be detected and further analyzes can be applied by using the methods mentioned.
Keywords
References
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Details
Primary Language
English
Subjects
Health Services and Systems (Other)
Journal Section
Research Article
Early Pub Date
March 15, 2024
Publication Date
March 31, 2024
Submission Date
December 1, 2023
Acceptance Date
February 19, 2024
Published in Issue
Year 2024 Volume: 14 Number: 1
APA
Demir, O., & Erkorkmaz, Ü. (2024). Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data. Sakarya Medical Journal, 14(1), 20-27. https://doi.org/10.31832/smj.1390306
AMA
1.Demir O, Erkorkmaz Ü. Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data. Sakarya Medical Journal. 2024;14(1):20-27. doi:10.31832/smj.1390306
Chicago
Demir, Osman, and Ünal Erkorkmaz. 2024. “Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis With Crimean-Congo Hemorrhagic Fever Data”. Sakarya Medical Journal 14 (1): 20-27. https://doi.org/10.31832/smj.1390306.
EndNote
Demir O, Erkorkmaz Ü (March 1, 2024) Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data. Sakarya Medical Journal 14 1 20–27.
IEEE
[1]O. Demir and Ü. Erkorkmaz, “Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data”, Sakarya Medical Journal, vol. 14, no. 1, pp. 20–27, Mar. 2024, doi: 10.31832/smj.1390306.
ISNAD
Demir, Osman - Erkorkmaz, Ünal. “Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis With Crimean-Congo Hemorrhagic Fever Data”. Sakarya Medical Journal 14/1 (March 1, 2024): 20-27. https://doi.org/10.31832/smj.1390306.
JAMA
1.Demir O, Erkorkmaz Ü. Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data. Sakarya Medical Journal. 2024;14:20–27.
MLA
Demir, Osman, and Ünal Erkorkmaz. “Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis With Crimean-Congo Hemorrhagic Fever Data”. Sakarya Medical Journal, vol. 14, no. 1, Mar. 2024, pp. 20-27, doi:10.31832/smj.1390306.
Vancouver
1.Osman Demir, Ünal Erkorkmaz. Use of Residuals and Rank Product in Detection of Outlier in Survival Analysis with Crimean-Congo Hemorrhagic Fever Data. Sakarya Medical Journal. 2024 Mar. 1;14(1):20-7. doi:10.31832/smj.1390306