单个协变量带有测量误差的多维结构回归模型被引量：1

The Multi-Dimensional Structural Regression Model with One-Dimensional Covariate and the Measurement Errors

下载PDF

导出

摘要给出可交换条件下单个协变量的带有测量误差的多维结构回归模型,利用该模型研究总体平均处理效应的估计,给出当暴露组和对照组的协变量测量误差同分布时总体平均处理效应的拟极大似然估计及其性质. In this paper,the multi-dimensional structural regression models with onedimensional covariate and the measurement errors under exchangeability condition are given.The models are studied to estimate the population-averaged treatment effects.When the measurement errors of the covariates in the treatment population and the control population have the same distributions,the quasi-maximum likelihood estimator of the population-averaged treatment effect and its characters are given.

作者何春方积乾

机构地区广东工业大学应用数学学院中山大学公共卫生学院

出处《生物数学学报》 CSCD 北大核心 2007年第2期311-316,共6页 Journal of Biomathematics

基金国家自然科学基金重点课题资助项目(39930160)

关键词总体平均处理效应多维结构回归模型协变量测量误差拟极大似然估计 The Population-averaged treatment effect Multi-dimensional structural regression model Covariate Measurement error Quasi-maximum likelihood estimator

分类号 O212.1 [理学—概率论与数理统计]

引文网络
相关文献

参考文献6

1何春,方积乾.可交换条件下多维结构回归模型总体平均处理效应的估计[J].生物数学学报,2003,18(3):321-327. 被引量：6
2金华,何春,方积乾.可交换条件下的结构回归模型[J].中山大学学报（自然科学版）,2003,42(3):4-7. 被引量：1
3Fuller W A.Measurement Error Models[M].New York:Wiley,1987.
4Carroll R,Ruppert D,Stefanski L Measurement Error in Nonlinear Models[M].New York:Wiley,1995.
5Greenland S,Robins J M,Pearl J.Confounding and Collapsibility in Causal Inference[J].Statistical Science,1999,14(1):29-46
6金华,方积乾.多维协变量具有测量误差的结构回归模型[J].生物数学学报,2005,20(1):77-82. 被引量：1

二级参考文献12

1ROSENBAUM P R, RUBIN D B. The central role of the propensity score in observational studies for causal effects[ J]. Biometrika, 1983,70:41 - 55.
2ROBINS J M, GREENLAND S. The role of model selection in causal inference from nonexperirnental data [ J ]. American Journal of Epidemiology, 1986,123:393 - 402.
3ROBINS J M,GREENLAND S.Adjusting for differential rates of prophylaxis therapy for PCP in high versus low dose AZT treatment arms in an AIDS randomized trial[J].J American Statistical Association, 1994,89: 737 - 749.
4ROBINS J M, RITOV Y. Toward a curse-of-dimemionality appropriate (CODA) asymptotic theory for semiparametric models[J]. Statistics in Medicine, 1997,16:285 - 319.
5Rosenbaum P R, Rubin D B. The central role of the propensity score in observational studies for causal effects[J]. Biometrika, 1983, 70(1):41-55.
6Robins J M, Greenland S. The role of model selection in causal inference from non-experimental data[J].American Journal of Epidemiology, 1986, 123(3):393-402.
7Robins J M, Greenland S. Adjusting for differential rates of prophylaxis therapy for POP in high versus low dose azt treatment arms in an aids randomized trial[J]. Journal of American Statistical Association, 1994,89:737-749.
8Robins J M, Ritov Y. Toward a curse-of-dimensionality appropriate (CODA) asymptotic theory for semiparametric models[J]. Statistics in Medicine, 1997, 16(1-3):285-319.
9Fuller W A. Measurement Error Models[M]. New York: Wiley, 1987.
10Carroll R, Ruppert D, Stefanski L. Measurement Error in Nonlinear Models[M]. New York: Wiley, 1995.