Exploring Objective Causal Inference in Case-Noncase Studies under the Rubin Causal Model

作者: Nikola Andric

DOI:

关键词: Causal inferenceStatisticsRubin causal modelPsychologyCovariateEconometricsLogistic regressionProbit modelBalance assessmentCausal analysis

摘要: investigated via simulation, and compared to those of logistic probit regression. Chapter 3 focuses on the re-analysis a subset data from published article, Karkouti et al. (2006). We investigate whether PrepDA regression, when applied case-noncase data, can generate estimates that are concordant with causal analysis prospectively collected data. introduce tools for covariate balance assessment across multiple imputed datasets. explore potential analyst bias said method is used analyze In 4 we discuss our technology’s advantages over, drawbacks as to, traditional approaches. iv

参考文章(57)
Olaf Gefeller, Annette Pfahlberg, Hermann Brenner, Jürgen Windeler, An empirical investigation on matching in published case-control studies. European Journal of Epidemiology. ,vol. 14, pp. 321- 325 ,(1998) , 10.1023/A:1007497104800
Robert McCulloch, Xiao Li Meng, John Barnard, Modeling covariance matrices in terms of standard deviations and correlations, with application to shrinkage Statistica Sinica. ,vol. 10, pp. 1281- 1311 ,(2000)
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
William G. Cochran, Donald B. Rubin, Controlling Bias in Observational Studies: A Review Matched Sampling for Causal Effects. pp. 30- 58 ,(1974) , 10.1017/CBO9780511810725.005
J.A. Anderson, LOGISTIC DISCRIMINATION WITH MEDICAL APPLICATIONS Discriminant Analysis and Applications. pp. 1- 15 ,(1973) , 10.1016/B978-0-12-154050-0.50008-3
Donald B Rubin, Causal Inference Using Potential Outcomes Journal of the American Statistical Association. ,vol. 100, pp. 322- 331 ,(2005) , 10.1198/016214504000001880
Xiao-Li Meng, Multiple-Imputation Inferences with Uncongenial Sources of Input Statistical Science. ,vol. 9, pp. 538- 558 ,(1994) , 10.1214/SS/1177010269