Marginal Mean Models for Dynamic Regimes.
作者： S A Murphy , M J van der Laan , J M Robins ,
DOI: 10.1198/016214501753382327
关键词:
摘要: A dynamic treatment regime is a list of rules for how the level will be tailored through time to an individual's changing severity. In general, individuals who receive highest are with greatest severity and need treatment. Thus, there planned selection dose. addition mandated by rules, staff judgment results in unplanned level. Given observational longitudinal data or which level, methodology proposed here allows estimation mean response under assumption sequential randomization.
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sci-hub.se 参考文章(28)
James M. Robins, Andrea Rotnitzky, Recovery of Information and Adjustment for Dependent Censoring Using Surrogate Markers Birkhäuser, Boston, MA. pp. 297- 331 ,(1992) , 10.1007/978-1-4757-1229-2_14
Jerzy Splawa-Neyman, D. M. Dabrowska, T. P. Speed, On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9 Statistical Science. ,vol. 5, pp. 465- 472 ,(1990) , 10.1214/SS/1177012031
James M. Robins, Larry Wasserman, Estimation of effects of sequential treatments by reparameterizing directed acyclic graphs uncertainty in artificial intelligence. pp. 409- 420 ,(1997)
James M. Robins, Andrea Rotnitzky, Daniel O. Scharfstein, Sensitivity Analysis for Selection bias and unmeasured Confounding in missing Data and Causal inference models Statistical Models in Epidemiology, the Environment, and Clinical Trials. ,vol. 116, pp. 1- 94 ,(2000) , 10.1007/978-1-4612-1284-3_1
James M. Robins, Causal Inference from Complex Longitudinal Data Springer, New York, NY. pp. 69- 117 ,(1997) , 10.1007/978-1-4612-1842-5_4
Donald B. Rubin, Statistics and Causal Inference: Comment: Which Ifs Have Causal Answers Journal of the American Statistical Association. ,vol. 81, pp. 961- ,(1986) , 10.2307/2289065
Paul W. Holland, Statistics and Causal Inference Journal of the American Statistical Association. ,vol. 81, pp. 945- 960 ,(1986) , 10.1080/01621459.1986.10478354
JAMES M. ROBINS, YA'ACOV RITOV, TOWARD A CURSE OF DIMENSIONALITY APPROPRIATE (CODA) ASYMPTOTIC THEORY FOR SEMI‐PARAMETRIC MODELS Statistics in Medicine. ,vol. 16, pp. 285- 319 ,(1997) , 10.1002/(SICI)1097-0258(19970215)16:3<285::AID-SIM535>3.0.CO;2-#
J. Aitchison, S. D. Silvey, Maximum-Likelihood Estimation of Parameters Subject to Restraints Annals of Mathematical Statistics. ,vol. 29, pp. 813- 828 ,(1958) , 10.1214/AOMS/1177706538
Daniel O. Scharfstein, Andrea Rotnitzky, James M. Robins, Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models Journal of the American Statistical Association. ,vol. 94, pp. 1096- 1120 ,(1999) , 10.1080/01621459.1999.10473862