We consider a Markov structure for partially unobserved time-varying compliance classes in the Imbens-Rubin (1997) compliance model framework. The context is a longitudinal randomized intervention study where subjects are randomized once at baseline, outcomes and patient adherence are measured at multiple follow-ups, and patient adherence to their randomized treatment could vary over time. We propose a nested latent compliance class model where we use time-invariant subject-specific compliance principal strata to summarize longtudinal trends of subject-specific time-varying compliance patterns. The principal strata are formed using Markov models that related current compliance behavior to compliance history. Treatment effects are estimated...
Compliance, the extent to which patients follow a medication regimen, has been recognized as one of ...
We propose a structural mean modeling approach to obtain compliance-adjusted estimates for treatment...
"Preface Latent Markov models represent an important class of latent variable models for the analysi...
We consider a Markov structure for partially unobserved time-varying compliance classes in the Imben...
We propose nested latent compliance class models for analyzing longitudinal randomized trials when s...
Lin et al. ( http://www.biostatsresearch.com/upennbiostat/papers/ , 2006) proposed a nested Markov...
This article discusses a nested latent class model for analyzing longitudinal randomized trials when...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108032/1/sim5811.pd
Much research in the social and health sciences aims to understand the causal relationship between a...
In the presence of non-compliance, conventional analysis by intention-to-treat provides an unbiased ...
AbstractObjectivesThere is evidence to suggest that noncompliant and nonpersistent behaviors have di...
Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requi...
Background: Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the thera...
This article considers the problem of assessing causal effect moderation in longitudinal settings in...
Background: Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the thera...
Compliance, the extent to which patients follow a medication regimen, has been recognized as one of ...
We propose a structural mean modeling approach to obtain compliance-adjusted estimates for treatment...
"Preface Latent Markov models represent an important class of latent variable models for the analysi...
We consider a Markov structure for partially unobserved time-varying compliance classes in the Imben...
We propose nested latent compliance class models for analyzing longitudinal randomized trials when s...
Lin et al. ( http://www.biostatsresearch.com/upennbiostat/papers/ , 2006) proposed a nested Markov...
This article discusses a nested latent class model for analyzing longitudinal randomized trials when...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108032/1/sim5811.pd
Much research in the social and health sciences aims to understand the causal relationship between a...
In the presence of non-compliance, conventional analysis by intention-to-treat provides an unbiased ...
AbstractObjectivesThere is evidence to suggest that noncompliant and nonpersistent behaviors have di...
Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requi...
Background: Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the thera...
This article considers the problem of assessing causal effect moderation in longitudinal settings in...
Background: Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the thera...
Compliance, the extent to which patients follow a medication regimen, has been recognized as one of ...
We propose a structural mean modeling approach to obtain compliance-adjusted estimates for treatment...
"Preface Latent Markov models represent an important class of latent variable models for the analysi...