×

Nonparametric and semiparametric estimation of quantile residual lifetime for length-biased and right-censored data. (English. French summary) Zbl 1474.62343

Summary: Quantile residual lifetime models are often of concern in survival analysis, especially when studying a chronic or irreversible disease like dementia. In the past several decades residual life models have been studied extensively with right-censored survival data. However these methods are not suitable to analyze the length-biased and right-censored data from the prevalent cohort sampling. In this article we propose nonparametric and semiparametric model-based procedures to estimate the quantile residual lifetime with censored length-biased data. Two test statistics are established for comparing the quantile residual lifetimes of two groups, evaluated, respectively, on ratio and difference in terms of type I error probabilities and powers. Some simulations are conducted to compare the proposed method with existing approaches. Real dementia data from the National Alzheimer’s Coordinating Center are used to illustrate the proposed estimation methods by estimating the quantile residual lifetimes of the dementia patients.

MSC:

62N01 Censored data models
62N02 Estimation in survival analysis and censored data
62N05 Reliability and life testing
62G08 Nonparametric regression and quantile regression
62P10 Applications of statistics to biology and medical sciences; meta analysis
Full Text: DOI

References:

[1] Addona, V. & Wolfson, D. B. (2006). A formal test for the stationarity of the incidence rate using data from a prevalent cohort study with follow‐up. Lifetime Data Analysis, 12, 267-284. · Zbl 1356.62059
[2] Andersen, P. K., Borgan, O., Gill, R. D., & Keiding, N. (1993). Statistical Models Based on Counting Processes. Springer Science, New York. · Zbl 0769.62061
[3] Andersen, P. K. & Gill, R. D. (1982). Cox’s regression model for counting processes: A large sample study. The Annals of Statistics, 10, 1100-1120. · Zbl 0526.62026
[4] Arnold, B. & Brockett, P. L. (1983). Technical note—When does the \(\beta\) th percentile residual lifetime function determine the distribution?Operations Research, 31, 391-396. · Zbl 0533.62087
[5] Asgharian, M. (2014). On the singularities of the information matrix and multipath change‐point problems. Theory of Probability and Its Applications, 58, 546-561. · Zbl 1310.62028
[6] Asgharian, M., M’Lan, C. M., & Wolfson, D. B. (2002). Length‐biased sampling with right censoring: An unconditional approach. Journal of the American Statistical Association, 97, 201-209. · Zbl 1073.62561
[7] Asgharian, M. & Wolfson, D. B. (2005). Asymptotoic behavior of the unconditional NPMLE of the length‐biased survivor function from right censored prevalent cohort data. The Annals of Statistics, 33, 2109-2131. · Zbl 1086.62113
[8] Chan, K. C. G. (2013). Survival analysis without survival data: Connecting length‐biased and case‐control data. Biometrika, 100, 764-770. · Zbl 1284.62613
[9] Chan, K. C. G., Chen, Y. Q., & Di, C. (2012). Proportional mean residual lifetime model for right‐censored length‐biased data. Biometrika, 99, 995-1000. · Zbl 1452.62798
[10] Chen, Y. Q. (2010). Semiparametric regression in size‐biased sampling. Biometrics, 66, 149-158. · Zbl 1187.62073
[11] Chen, Y. Q. & Cheng, S. (2005). Semiparametric regression analysis of mean residual lifetime with censored data. Biometrika, 92, 19-29. · Zbl 1068.62044
[12] Chen, Y. Q. & Cheng, S. (2006). Linear lifetime expectancy regression with censored data. Biometrika, 93, 303-313. · Zbl 1153.62359
[13] Chen, Y. Q., Jewell, N. P., Lei, X., & Cheng, S. C. (2005). Semiparametric estimation of proportional mean residual lifetime model in presence of censoring. Biometrics, 61, 170-178. · Zbl 1077.62079
[14] Chiang, C. L. (1960). A stochastic study of the lifetime table and its applications: I. Probability distributions of the biometric functions. Biometrics, 16, 618-635. · Zbl 0104.13903
[15] Cox, D. R. (1962). Renewal Theory. Methuen, London. · Zbl 0103.11504
[16] Cox, D. R. (1972). Regression models and lifetime‐tables (with discussion). Journal of the Royal Statisitcal Society Series B, 34, 187-220. · Zbl 0243.62041
[17] Hebert, L. E., Weuve, J., Scherr, P. A., & Evans, D. A. (2013). Alzheimer disease in the United States (2010-2050) estimated using the 2010 census. Neurology, 80, 1778-1783.
[18] Huang, C. Y. & Qin, J. (2011). Nonparametric estimation for length‐biased and right‐censored data. Biometrika, 98, 177-186. · Zbl 1215.62032
[19] Huang, C. Y. & Qin, J. (2012). Composite partial likelihood estimation under length‐biased sampling, with application to a prevalent cohort study of Dementia. Journal of the American Statistical Association, 107, 946-957. · Zbl 1299.62123
[20] Jeong, J. & Fine, J. P. (2009). A note on cause‐specific residual lifetime. Biometrika, 96, 237-242. · Zbl 1163.62086
[21] Jeong, J. & Fine, J. P. (2013). Nonparametric inference on cause‐specific quantile residual lifetime. Biometrical Journal, 55, 68-81. · Zbl 1441.62387
[22] Jeong, J., Jung, S., & Costantiono, J. P. (2008). Nonparametric inference on median residual lifetime function. Biometrics, 64, 157-163. · Zbl 1138.62075
[23] Joe, H. & Proschan, F. (1984). Percentile residual lifetime functions. Operations Research, 32, 668-678. · Zbl 0558.62084
[24] Jung, S., Jeong, J., & Bandos, H. (2009). Regression on quantile residual lifetime. Biometrics, 65, 1203-1212. · Zbl 1180.62172
[25] Kaplan, E. L. & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53, 457-481. · Zbl 0089.14801
[26] Kosorok, M. R. (2008). Introduction to Empirical Processes and Semiparametric Inference. Springer‐Verlag, New York. · Zbl 1180.62137
[27] Lancaster, T. (1990). The Econometric Analysis of Transition Data. Cambridge University Press, Cambridge. · Zbl 0717.62106
[28] Lin, C., Zhang, L., & Zhou, Y. (2015). Conditional quantile residual lifetime models for right censored data. Lifetime Data, 21, 75-96. · Zbl 1322.62232
[29] Liu, P., Wang, Y., & Zhou, Y. (2014). Quantile residual lifetime with right‐censored and length‐biased data. Annals of the Institute of Statistical Mathematics, http://link.springer.com/article/10.1007
[30] Ma, Y. & Wei, Y. (2012). Analysis on censored quantile residual lifetime model via spline smoothing. Statistical Sinica, 22, 47-68. · Zbl 1417.62282
[31] Ma, Y. & Yin, G. (2010). Semiparametric median residual lifetime model and inference. Canadian Journal of Statistics, 38, 665-679. · Zbl 1349.62466
[32] Maguluri, G. & Zhang, C. ‐H. (1994). Estimation in the mean residual lifetime regression model. Journal of the Royal Statistical Society Series B, 56, 477-489. · Zbl 0803.62083
[33] Oakes, D. & Dasu, T. (1990). A note on residual lifetime. Biometrika, 77, 409-410. · Zbl 0713.62018
[34] Pakes, A. & Pollard, D. (1989). Simulation and the asymptotics of optimization estimators. Econometrica, 57, 1027-1057. · Zbl 0698.62031
[35] Schmittlein, D. C. & Morrison, D. G. (1981). The median residual lifetime: A characterization theorem and an application. Operations Research, 29, 392-399. · Zbl 0477.60083
[36] Shen, Y., Ning, J., & Qin, J. (2009). Analyzing length‐biased data with semiparametric transformation and accelerated failure time models. Journal of American Statistical Association, 104, 1192-1202. · Zbl 1388.62294
[37] Su, J. Q. & Wei, L. J. (1993). Nonparametric estimation for the difference or ratio of median failure times. Biometrics, 49, 603-607.
[38] Sun, L. Q. & Zhang, Z. (2009). A class of transformed mean residual lifetime models with censored survival data. Journal of the American Statistical Association, 104, 803-815. · Zbl 1388.62288
[39] Sun, L., Song, X., & Zhang, Z. (2012). Mean residual lifetime models with time‐dependent coefficients under right censoring. Biometrika, 99, 185-197. · Zbl 1234.62129
[40] Tsai, W. ‐Y., Jewell, N. P., & Wang, M. ‐C. (1987). A note on the product‐limit estimator under right censoring and left truncation. Biometrika, 74, 883-886. · Zbl 0628.62101
[41] Van der Vaart, A. W. & Wellner, J. A. (1996). Weak Convergence and Empirical Processes with Applications to Statistics. Springer‐Verlag, New York. · Zbl 0862.60002
[42] Wang, M. ‐C. (1991). Nonparametric estimation from cross‐sectional survival data. Journal of the American Statistical Association, 86, 130-143. · Zbl 0739.62026
[43] Wang, Y., Liu, P., & Zhou, Y. (2015). Quantile residual lifetime for left‐truncated and right‐censored data. Science China Mathematics, 58, 1217-1234. · Zbl 1327.62489
[44] Zeng, D. & Lin, D. Y. (2008). Efficient resampling methods for nonsmooth estimating function. Biostatistics, 9, 355-363. · Zbl 1143.62025
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.