Empirical simulation extrapolation for measurement error models with replicate measurements

被引：43

作者：

Devanarayan, V

Stefanski, LA

机构：

[1] Eli Lilly & Co, Lilly Res Labs, Indianapolis, IN 46285 USA

[2] N Carolina State Univ, Dept Stat, Raleigh, NC 27695 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2002年 / 59卷 / 03期

关键词：

errors-in-variables; heteroscedasticity; logistic regression; method of moments; simulation; variance components;

D O I：

10.1016/S0167-7152(02)00098-6

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We present a variation of the simex algorithm (J. Amer. statist. Assoc. 89 (1994) 1314) appropriate for the case in which the measurement error variance(s) are unknown but replicate measurements are available. The method used pseudo errors generated from random linear contrasts of the observed replicate measurements. An attractive feature of the new method is its ability to accommodate heteroscedastic measurement error. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：219 / 225

页数：7

共 13 条

[1] Asymptotics for the SIMEX estimator in nonlinear measurement error models [J].