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强可忽略处理分配下因果推断的结构回归模型 被引量：4

STRUCTURAL REGRESSION MODEL FOR CAUSAL INFERENCE UNDER STRONGLY IGNORABLE TREATMENT ASSIGNMENT
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摘要 建立强可忽略处理分配条件下因果推断的结构回归模型，估计平均处理效应．在正态分布假 设下，总体参数的极大似然估计是渐近正态无偏估计．提出的方法可推广到具有测量误差的一般情 形． A structural regression model for causal inference is established to estimate the average treatment effect under strongly ignorable treatment assignment. Under the normal distribution, the maximum likelihood estimator for the population parameter is proved to be unbiased and asymptotically normal. The proposed method can be applied to the general case with measurement errors.
作者 金华 方积乾
机构地区 华南师范大学数学系 中山医科大学卫生统计教研室
出处 《华南师范大学学报（自然科学版）》 CAS 2000年第4期7-12,共6页 Journal of South China Normal University(Natural Science Edition)
基金 国家自然科学基金重点项目!(39930160)资助课题
关键词 因果推断 强可忽略处理分析 结构回归模型 causal inference strongly ignorable treatment assignment structural regression model average treatment effect maximum likelihood estimator asymptotically normal.
分类号 O212.1 [理学—概率论与数理统计]
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参考文献6

  • 1[1] Dawid A P. Conditional Independence in Statistical Theory [J]. Journal of the Royal Statistical Society, 1979(Ser. B), 41: 1～31.
  • 2[2] Rosenbaum P R， Rubin D B. The Central Role of the Propensity Score in Observational Studies for Causal Effects [J]. Biometrika, 1983, 70: 41～55.
  • 3[3] Robins J M， Greenland S. The Role of Model Selection in Causal Inference from Nonexperimental Data [J]. American Journal of Epidemiology, 1986, 123: 393～402.
  • 4[4] Greenland S, Robins J M, Pearl J. Confounding and Collapsibility in Causal Inference [J]. Statistical Science, 1999, 14(1): 29～46.
  • 5[5] Robins 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]. Journal of American Statistical Association, 1994, 89: 737～749.
  • 6[6] Robins J M， Ritov Y. Toward a Curse-of-dimensionality Appropriate (CODA) Asymptotic Theory for Semiparametric Models [J]. Statistics in Medicine, 1997, 16: 285～319.

同被引文献17

  • 1赵慧,郑忠国,许静.含隐变量和选择偏差的图模型中的因果推断[J].北京大学学报（自然科学版）,2006,42(5):584-589. 被引量：4
  • 2Rosenbaum 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.
  • 3Robins 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.
  • 4Robins 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.
  • 5Robins 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.
  • 6Fuller W A. Measurement Error Models[M]. New York: Wiley, 1987.
  • 7Carroll R, Ruppert D, Stefanski L. Measurement Error in Nonlinear Models[M]. New York: Wiley, 1995.
  • 8Greenland S, RobinsJ M, Pearl J. Confounding and collapsibility in causal inference[J]. Statistical Science,1999, 14(1):29-46.
  • 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.

引证文献4

二级引证文献9

华南师范大学学报（自然科学版）
2000年 第4期

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