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Keywords:
accelerated failure time model; survival analysis; goodness-of-fit
accelerated failure time model; survival analysis; goodness-of-fit
Summary:
The Accelerated Failure Time model presents a way to easily describe survival regression data. It is assumed that each observed unit ages internally faster or slower, depending on the covariate values. To use the model properly, we want to check if observed data fit the model assumptions. In present work we introduce a goodness-of-fit testing procedure based on modern martingale theory. On simulated data we study empirical properties of the test for various situations.
References:
[1] Bagdonavičius, V., Nikulin, M.: Accelerated Life Models. Chapman and Hall / CRC, Boca Raton 2002. Zbl 1127.62410
[2] Buckley, J., James, I. R.: Linear regression with censored data. Biometrika 66 (1979), 429-436. DOI 10.1093/biomet/66.3.429 | Zbl 0425.62051
[3] Cox, D. R.: Regression models and life tables. J. Roy. Statist. Soc. Ser. B 34 (1972), 187-220. MR 0341758 | Zbl 0243.62041
[4] Cox, D. R., D.Oakes: Analysis of Survival Data. Chapman and Hall / CRC, Boca Raton1984. MR 0751780 | Zbl 0900.62605
[5] Fleming, T. R., Harrington, D. P.: Counting Processes and Survival Analysis. Wiley, New York 1991. MR 1100924 | Zbl 1079.62093
[6] Lin, D. Y., Spiekerman, C. F.: Model checking techniques for parametric regression with censored data. Scand. J. Statist. 23 (1996), 157-177. MR 1394651 | Zbl 0854.62081
[7] Lin, D. Y., Wei, L. J., Ying, Z.: Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika 80 (1993), 557-572. DOI 10.1093/biomet/80.3.557 | MR 1248021 | Zbl 0788.62094
[8] Lin, D. Y., Wei, L. J., Ying, Z.: Accelerated failure time models for counting processes. Biometrika 85 (1998), 605-618. DOI 10.1093/biomet/85.3.605 | MR 1665810 | Zbl 0947.62069
[9] Lin, D. Y., Ying, Z.: Semiparametric inference for the accelerated life model with time-dependent covariates. J. Statist. Plann. Inference 44 (1995), 47-63. DOI 10.1016/0378-3758(94)00039-X | MR 1323070 | Zbl 0812.62096
[10] Pollard, D.: Empirical Processes: Theory and Applications. Hayward, California: IMS 1990. MR 1089429 | Zbl 0741.60001
[11] Shorack, G. R., Wellner, J. A.: Empirical Processes with Applications to Statistics. Wiley, New York 1986. MR 0838963 | Zbl 1171.62057
[12] Silverman, B. W.: Density Estimation for Statistics and Data Analysis. Chapman and Hall, London 1986. MR 0848134 | Zbl 0617.62042
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