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單一檢測時間二元現時狀態數據之獨立性檢定 = Testing indep...

國立高雄大學統計學研究所

單一檢測時間二元現時狀態數據之獨立性檢定 = Testing independence for bivariate current status data with common monitoring time

Record Type:	Language materials, printed : monographic
Paralel Title:	Testing independence for bivariate current status data with common monitoring time
Author:	田世州,
Secondary Intellectual Responsibility:	國立高雄大學
Place of Publication:	[高雄市]
Published:	撰者;
Year of Publication:	2014[民103]
Description:	76面圖，表 : 30公分;
Subject:	Mantel-Haenszel檢定方法
Subject:	Mantel-Haenszel test
Online resource:	http://handle.ncl.edu.tw/11296/ndltd/27384425350467802131
Notes:	105年10月25日公開
Notes:	參考書目：面19-20
Summary:	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.

單一檢測時間二元現時狀態數據之獨立性檢定 = Testing independence for bivariate current status data with common monitoring time
田, 世州

單一檢測時間二元現時狀態數據之獨立性檢定 = Testing independence for bivariate current status data with common monitoring time / 田世州撰 - [高雄市] : 撰者, 2014[民103]. - 76面 ; 圖，表 ; 30公分.
105年10月25日公開參考書目：面19-20.
Mantel-Haenszel檢定方法Mantel-Haenszel test

單一檢測時間二元現時狀態數據之獨立性檢定 = Testing independence for bivariate current status data with common monitoring time
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330 $a 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.
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