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Full-Text Articles in Statistics and Probability
Simultaneously Optimizing Dose And Schedule Of A New Cytotoxic Agent, Thomas M. Braun, Peter F. Thall, Hoang Nguyen, Marcos De Lima
Simultaneously Optimizing Dose And Schedule Of A New Cytotoxic Agent, Thomas M. Braun, Peter F. Thall, Hoang Nguyen, Marcos De Lima
The University of Michigan Department of Biostatistics Working Paper Series
Traditionally, phase I clinical trial designs determine a maximum tolerated dose of an experimental cytotoxic agent based on a fixed schedule, usually one course consisting of multiple administrations, while varying the dose per administration between patients. However, in actual medical practice patients often receive several courses of treatment, and some patients may receive one or more dose reductions due to low-grade (non-dose limiting) toxicity in previous courses. As a result, the overall risk of toxicity for each patient is a function of both the schedule and the dose used at each adminstration. We propose a new paradigm for Phase I …
Nested Markov Compliance Class Model In The Presence Of Time-Varying Noncompliance, Julia Y. Lin, Thomas R. Tenhave, Michael R. Elliott
Nested Markov Compliance Class Model In The Presence Of Time-Varying Noncompliance, Julia Y. Lin, Thomas R. Tenhave, Michael R. Elliott
UPenn Biostatistics Working Papers
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 as intent-to …
Causal Comparisons In Randomized Trials Of Two Active Treatments: The Effect Of Supervised Exercise To Promote Smoking Cessation, Jason Roy, Joseph W. Hogan
Causal Comparisons In Randomized Trials Of Two Active Treatments: The Effect Of Supervised Exercise To Promote Smoking Cessation, Jason Roy, Joseph W. Hogan
COBRA Preprint Series
In behavioral medicine trials, such as smoking cessation trials, two or more active treatments are often compared. Noncompliance by some subjects with their assigned treatment poses a challenge to the data analyst. Causal parameters of interest might include those defined by subpopulations based on their potential compliance status under each assignment, using the principal stratification framework (e.g., causal effect of new therapy compared to standard therapy among subjects that would comply with either intervention). Even if subjects in one arm do not have access to the other treatment(s), the causal effect of each treatment typically can only be identified from …
Longitudinal Nested Compliance Class Model In The Presence Of Time-Varying Noncompliance, Julia Y. Lin, Thomas R. Tenhave, Michael R. Elliott
Longitudinal Nested Compliance Class Model In The Presence Of Time-Varying Noncompliance, Julia Y. Lin, Thomas R. Tenhave, Michael R. Elliott
UPenn Biostatistics Working Papers
This article discusses a nested latent class model for analyzing longitudinal randomized trials when subjects do not always adhere to the treatment to which they are randomized. In the "Prevention of Suicide in Primary Care Elderly: Collaborative Trial" (PROSPECT) study, subjects were randomized to either the control treatment, where they received standard care, or to the intervention, where they received standard care in addition to meeting with depression health specialists. The health specialists educate patients, their families, and physicians about depression and monitor their treatment. Those randomized to the control treatment have no access to the health specialists; however, those …
Semiparametric Bayesian Modeling Of Multivariate Average Bioequivalence, Pulak Ghosh Dr., Mithat Gonen
Semiparametric Bayesian Modeling Of Multivariate Average Bioequivalence, Pulak Ghosh Dr., Mithat Gonen
Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series
Bioequivalence trials are usually conducted to compare two or more formulations of a drug. Simultaneous assessment of bioequivalence on multiple endpoints is called multivariate bioequivalence. Despite the fact that some tests for multivariate bioequivalence are suggested, current practice usually involves univariate bioequivalence assessments ignoring the correlations between the endpoints such as AUC and Cmax. In this paper we develop a semiparametric Bayesian test for bioequivalence under multiple endpoints. Specifically, we show how the correlation between the endpoints can be incorporated in the analysis and how this correlation affects the inference. Resulting estimates and posterior probabilities ``borrow strength'' from one another …