Since Partin introduced the analysis of prostate-specific antigen, clinical T-stage and Gleason scores to estimate the risk of progression in men with localised prostate cancer, our understanding of factors that modify this risk has changed drastically. There are now multiple risk stratification tools available, including look-up tables, risk stratification/classification analyses, regression-t...

Pearl (2011) asked for the causal inference community to clarify the role of the principal stratification framework in the analysis of causal effects. Here, I argue that the notion of principal stratification has shed light on problems of non-compliance, censoring-by-death, and the analysis of post-infection outcomes; that it may be of use in considering problems of surrogacy but further develo...

Background: Mortality and major adverse cardiac events (MACE) frequently occur after percutaneous coronary intervention (PCI). Therefore, the ability to predict such events through an established risk stratification method is of great importance. The present study was aimed at determining the risk stratification of mortality and MACE in post-PCI patients at the intensive cardiac care unit of Ci...

We prove that the standard nonparametric mean estimator for judgment post-stratification is inadmissible under squared error loss within a certain class of linear estimators. We derive alternate estimators that are admissible in this class, and we show that one of them is always better than the standard estimator. The reduction in mean squared error from using this alternate estimator can be as...

BACKGROUND Several scores, most of which were derived from clinical trials, have been proposed for stratifying risk after myocardial infarctions (MIs). Little is known about their generalizability to the community, their respective advantages, and whether the ejection fraction (EF) adds prognostic information to the scores. The purpose of this study is to evaluate the Thrombolysis in Myocardial...

Post-stratification estimation is a technique used in sample surveys to improve efficiency of estimators. Survey weights are adjusted to force the estimated numbers of units in each of a set of estimation cells to be equal to known population totals. The resulting weights are then used in forming estimates of means or totals of variables collected in the survey. For example, in a household surv...

This paper empirically compares three estimation methods—regression, calibration, and principal person— used in a household survey for post-stratification. Posttratification is important in many household surveys to adjust for nonresponse and the population undercount that esults from frame deficiencies. The correction for population undercoverage is usually achieved by adjusting estimated peop...