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研究生:田世州
研究生(外文):Shih-jhou Tian
論文名稱:單一檢測時間二元現時狀態數據之獨立性檢定
論文名稱(外文):Testing independence for bivariate current status data with common monitoring time
指導教授:黃錦輝黃錦輝引用關係
指導教授(外文):Kam-Fai Wong
學位類別:碩士
校院名稱:國立高雄大學
系所名稱:統計學研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:英文
論文頁數:76
中文關鍵詞:Mantel-Haenszel檢定方法現時狀態數據2×2列聯表無母數分析方法Sieve估計法
外文關鍵詞:Mantel-Haenszel testCurrent status dataTwo-by-two tableNonparametric analysisSieve estimation
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這篇文章中基於單一檢測時間之二元現時狀態數據,提供一種無母數檢定方法,檢定其邊際存活函數是否獨立。有別於使用無母數最大概似估計法收斂速率為n^(1/3)之邊際存活函數估計,在此考慮Sieve估計量以得到任意收斂速率的邊際存活函數估計。文中除了提供建構之檢定統計量之大樣本推論,亦透過統計模擬探討有限樣本下該檢定統計量的可行性.由模擬結果發現,邊際存活函數之估計量在收斂速率在n^(3/8)時檢定力最大。
This article develops a nonparametric procedure for testing marginal independence based on bivariate current status data with common monitoring time. Instead of using nonparametric maximum likelihood technique to estimate the marginal survival function, the Sieve estimator technique is applied so that not only the convergence rate of the marginal survival function at n^(1/3) be considered. Asymptotic properties of the proposed tests are derived, and their finite sample performance is studied via simulation. The simulation results show that the test statistic with convergence rate of the marginal survival function at n^(3/8) gives the most power in almost all the cases and have larger power than all the recent methods in all cases.
List of table ii
中文摘要 iv
英文摘要 v
1. Introduction……………………………………………………………………1
2. Preliminaries.………………………………………………………………3
3. The Proposed Method…………………………………………………5
4. Simulation…………………………………………………………………………8
4.1 Generating the bivariate current status data based on a copula model…8
4.2 Simulation studies………………………………………………9
5. Discussion………………………………………………………………………12
Appendix A………………………………………………………………………………13
Appendix B………………………………………………………………………………14
References………………………………………………………………………………19
[1] Aragon, J., Rabinowitz, D. and Tsiatis, A. (1995), “Regression With Interval Censored Data,” Biometrika, 82, 501–513.
[2] Ayer, M., Brunk, H. D., Ewing, G. M., Reid, W. T. and Silverman, E. (1995), “An Empirical Distribution for Sampling with Incomplete Observations,” The Annals of Mathematical Statistics, 26, 641-647.
[3] Cheng, G. and Wang, X. (2011), “Semiparametric Additive Transformation Model Under Current Status Data,” Electronic Journal of Statistics, 5, 1735-1764.
[4] Clayton, D. G. (1978), “A Model for Association in Bivariate Life Table and Its Application in Epidemiological Atudies of Familial Tendency in Chronic Disease Incidence,” Biometrika, 65, 141-151.
[5] Ding, A. A. and Wang, W. (2000), “On Assessing the Association for Bivariate Current Status Data,” Biometrika, 87, 879–893.
[6] Ding, A. A. and Wang, W. (2004), “Testing Independence for Bivariate Current Status Data,” Journal of the American Statistical Association, 99, 145-155
[7] Finkelstein, D. M. (1986), “A Proportional Hazards Model for Interval Censored Failure Time Data,” Biometrika, 42, 845-854.
[8] Genest, C. (1987), “Frank’s Family of Bivariate Distributions,” Biometrika, 74,549–555.
[9] Groeneboom, P. and Wellner, J. A. (1992), Information Bounds and Non-Parametric Maximum Likelihood Estimation, Boston: Birkhauser.
[10] Hsu, L. and Prentice, R. L. (1996), “A Generalization of Mantel-Haenszel Test to Bivariate Failure Time Data,” Biometrika, 83, 905–911.
[11] Huang, J. and Wellner, J. A. (1995), “Asymptotic Normality of the NPMLE of Linear Functionals for Interval Censored Data, Case 1,” Statistica Neeriandica, 49, 153–163.
[12] Lam, K. F. and Xue, H. (2005), “A Semiparametric Regression Cure Model with Current Status Data,” Biometrika, 92, 573-586.
[13] Lin, D. Y., Oakes, D. and Ying, Z. (1998), “Additive Hazards Regression with Current Status Data,” Biometrika, 85, 289–298.
[14] Louis, T. A. and Shih, J. H. (1996), “Tests of Independence for Bivariate Survival Data,” Biometrics, 52, 1440–1449.
[15] Oakes, D. (1982), “A Concordance Test for Independence in the Presence of Bivariate Censoring,” Biometrics, 38, 451–455.
[16] Rossini, A. J. and Tsiatis, A. A. (1996), “A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data,” Journal of the American Statistical Association, 91, 713–721.
[17] Tsai, W. Y. and Wong, K. F. (2004), “A Generalization of Mantel-Haenszel Test to Bivariate Current Status Data”. Technical Report, Institute of Statistic National University of Kaohsiung.
[18] Turnbull, B. W. (1976), “The Empirical Distribution Function With Arbitrarily Grouped, Censored and Truncated Data,” Journal of the Royal Statistical Society, Ser. B, 38, 290–295.
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