Share Email Print
cover

Proceedings Paper

Advantage of the modified Lunn-McNeil technique over Kalbfleisch-Prentice technique in competing risks
Author(s): Iing Lukman; Noor Akma Ibrahim; Isa Bin Daud; Fauziah Maarof; Mohd Nasir Hassan
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Survival analysis algorithm is often applied in the data mining process. Cox regression is one of the survival analysis tools that has been used in many areas, and it can be used to analyze the failure times of aircraft crashed. Another survival analysis tool is the competing risks where we have more than one cause of failure acting simultaneously. Lunn-McNeil analyzed the competing risks in the survival model using Cox regression with censored data. The modified Lunn-McNeil technique is a simplify of the Lunn-McNeil technique. The Kalbfleisch-Prentice technique is involving fitting models separately from each type of failure, treating other failure types as censored. To compare the two techniques, (the modified Lunn-McNeil and Kalbfleisch-Prentice) a simulation study was performed. Samples with various sizes and censoring percentages were generated and fitted using both techniques. The study was conducted by comparing the inference of models, using Root Mean Square Error (RMSE), the power tests, and the Schoenfeld residual analysis. The power tests in this study were likelihood ratio test, Rao-score test, and Wald statistics. The Schoenfeld residual analysis was conducted to check the proportionality of the model through its covariates. The estimated parameters were computed for the cause-specific hazard situation. Results showed that the modified Lunn-McNeil technique was better than the Kalbfleisch-Prentice technique based on the RMSE measurement and Schoenfeld residual analysis. However, the Kalbfleisch-Prentice technique was better than the modified Lunn-McNeil technique based on power tests measurement.

Paper Details

Date Published: 12 March 2002
PDF: 9 pages
Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); doi: 10.1117/12.460229
Show Author Affiliations
Iing Lukman, Univ. Putra Malaysia (Malaysia)
Noor Akma Ibrahim, Univ. Putra Malaysia (Malaysia)
Isa Bin Daud, Univ. Putra Malaysia (Malaysia)
Fauziah Maarof, Univ. Putra Malaysia (Malaysia)
Mohd Nasir Hassan, Univ. Putra Malaysia (Malaysia)


Published in SPIE Proceedings Vol. 4730:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV
Belur V. Dasarathy, Editor(s)

© SPIE. Terms of Use
Back to Top