Joint modeling compliance and outcome for causal analysis in longitudinal studies
- Gao, Xin
- Brown, Gregory K.
- Elliott, Michael R.
DOIAbstract
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108032/1/sim5811.pd
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108032/1/sim5811.pd
We propose a structural mean modeling approach to obtain compliance-adjusted estimates for treatment...
We consider the analysis of clinical trials that involve randomization to an active treatment ( T =...
Non-compliance is very common in randomized experiments involving human participants. The intent-to-...
Much research in the social and health sciences aims to understand the causal relationship between a...
Data analysis for randomized trials including multitreatment arms is often complicated by subjects w...
We consider a Markov structure for partially unobserved time-varying compliance classes in the Imben...
In the presence of non-compliance, conventional analysis by intention-to-treat provides an unbiased ...
We propose nested latent compliance class models for analyzing longitudinal randomized trials when s...
Noncompliance is a common problem in randomized trials. When there is noncompliance, there is often ...
This article discusses a nested latent class model for analyzing longitudinal randomized trials when...
In behavioral medicine trials, such as smoking cessation trials, two or more active treatments are o...
Lin et al. ( http://www.biostatsresearch.com/upennbiostat/papers/ , 2006) proposed a nested Markov...
It is well established that a randomized controlled trial (RCT) is the gold standard design for medi...
We present a random effects logistic approach for estimating the efficacy of treatment for compliers...
Thesis (Ph.D.)--University of Washington, 2015-12Subject noncompliance is a common problem in the an...
We propose a structural mean modeling approach to obtain compliance-adjusted estimates for treatment...
We consider the analysis of clinical trials that involve randomization to an active treatment ( T =...
Non-compliance is very common in randomized experiments involving human participants. The intent-to-...
Much research in the social and health sciences aims to understand the causal relationship between a...
Data analysis for randomized trials including multitreatment arms is often complicated by subjects w...
We consider a Markov structure for partially unobserved time-varying compliance classes in the Imben...
In the presence of non-compliance, conventional analysis by intention-to-treat provides an unbiased ...
We propose nested latent compliance class models for analyzing longitudinal randomized trials when s...
Noncompliance is a common problem in randomized trials. When there is noncompliance, there is often ...
This article discusses a nested latent class model for analyzing longitudinal randomized trials when...
In behavioral medicine trials, such as smoking cessation trials, two or more active treatments are o...
Lin et al. ( http://www.biostatsresearch.com/upennbiostat/papers/ , 2006) proposed a nested Markov...
It is well established that a randomized controlled trial (RCT) is the gold standard design for medi...
We present a random effects logistic approach for estimating the efficacy of treatment for compliers...
Thesis (Ph.D.)--University of Washington, 2015-12Subject noncompliance is a common problem in the an...
We propose a structural mean modeling approach to obtain compliance-adjusted estimates for treatment...
We consider the analysis of clinical trials that involve randomization to an active treatment ( T =...
Non-compliance is very common in randomized experiments involving human participants. The intent-to-...
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