The Principal Stratification method estimates a causal intervention effect by taking account of subjects\u27 differences in participation, adherence or compliance. The current Principal Stratification method has been mostly used in randomized intervention trials with randomization at a single (individual) level with subjects who were randomly assigned to either intervention or control condition. However, randomized intervention trials have been conducted at group level instead of individual level in many scientific fields. This is so called two-level randomization , where randomization is conducted at a group (second) level, above an individual level but outcome is often observed at individual level within each group. The incorrect inferen...
<p>Two-stage randomization is a powerful design for estimating treatment effects in the presence of ...
We consider studies for evaluating the short-term effect of a treatment of interest on a time-to-eve...
Thesis (Ph.D.)--University of Washington, 2015This study utilizes a data driven simulation design, w...
Much research in the social and health sciences aims to understand the causal relationship between a...
In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often ...
Over the past decade, the generalizability of randomized experiments, defined as the level of consis...
Over the past decade, the generalizability of randomized experiments, defined as the level of consis...
Principal stratification has recently become a popular tool to address certain causal inference ques...
In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often ...
Infectious disease prevention studies often aim to test or estimate the "causal effect" of a prevent...
In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often ...
The ICH E9(R1) addendum (2019) proposed principal stratification (PS) as one of five strategies for ...
In randomized studies, treatment comparisons conditional on intermediate post-randomization outcomes...
In randomized studies, treatment comparisons conditional on intermediate post-randomization outcomes...
Principal stratification is a causal framework to analyse randomized experiments with a post-treatme...
<p>Two-stage randomization is a powerful design for estimating treatment effects in the presence of ...
We consider studies for evaluating the short-term effect of a treatment of interest on a time-to-eve...
Thesis (Ph.D.)--University of Washington, 2015This study utilizes a data driven simulation design, w...
Much research in the social and health sciences aims to understand the causal relationship between a...
In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often ...
Over the past decade, the generalizability of randomized experiments, defined as the level of consis...
Over the past decade, the generalizability of randomized experiments, defined as the level of consis...
Principal stratification has recently become a popular tool to address certain causal inference ques...
In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often ...
Infectious disease prevention studies often aim to test or estimate the "causal effect" of a prevent...
In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often ...
The ICH E9(R1) addendum (2019) proposed principal stratification (PS) as one of five strategies for ...
In randomized studies, treatment comparisons conditional on intermediate post-randomization outcomes...
In randomized studies, treatment comparisons conditional on intermediate post-randomization outcomes...
Principal stratification is a causal framework to analyse randomized experiments with a post-treatme...
<p>Two-stage randomization is a powerful design for estimating treatment effects in the presence of ...
We consider studies for evaluating the short-term effect of a treatment of interest on a time-to-eve...
Thesis (Ph.D.)--University of Washington, 2015This study utilizes a data driven simulation design, w...