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20182021
most citedSample size considerations for comparing dynamic treatment regimens in a sequential multiple-assignment randomized trial with a continuous longitudinal outcome

20 citations · 25 across the 7 of their papers we have counts for

collaborators

7 papers

stat.ME2021

A non-parametric Bayesian approach for adjusting partial compliance in sequential decision making

Indrabati Bhattacharya, Brent A. Johnson, William Artman +4

Existing methods in estimating the mean outcome under a given dynamic treatment regime rely on intention-to-treat analyses which estimate the effect of following a certain dynamic…

stat.ME2021

Sample size estimation for comparing dynamic treatment regimens in a SMART: a Monte Carlo-based approach and case study with longitudinal overdispersed count outcomes

Jamie Yap, John J. Dziak, Raju Maiti +4

Dynamic treatment regimens (DTRs), also known as treatment algorithms or adaptive interventions, play an increasingly important role in many health domains. DTRs are motivated to a…

stat.ME2020★ 3 cited

Bayesian Set of Best Dynamic Treatment Regimes and Sample Size Determination for SMARTs with Binary Outcomes

William J. Artman, Ashkan Ertefaie, Kevin G. Lynch +1

One of the main goals of sequential, multiple assignment, randomized trials (SMART) is to find the most efficacious design embedded dynamic treatment regimes. The analysis method k…

stat.ME2020★ 1 cited

Adjusting for Partial Compliance in SMARTs: a Bayesian Semiparametric Approach

William J. Artman, Ashkan Ertefaie, Kevin G. Lynch +2

The cyclical and heterogeneous nature of many substance use disorders highlights the need to adapt the type or the dose of treatment to accommodate the specific and changing needs…

stat.ME2020

Robust Q-learning

Ashkan Ertefaie, James R. McKay, David Oslin +1

Q-learning is a regression-based approach that is widely used to formalize the development of an optimal dynamic treatment strategy. Finite dimensional working models are typically…

stat.ME2018★ 20 cited

Sample size considerations for comparing dynamic treatment regimens in a sequential multiple-assignment randomized trial with a continuous longitudinal outcome

Nicholas J. Seewald, Kelley M. Kidwell, Inbal Nahum-Shani +3

Clinicians and researchers alike are increasingly interested in how best to personalize interventions. A dynamic treatment regimen (DTR) is a sequence of pre-specified decision rul…

stat.AP2018★ 1 cited

Power Analysis in a SMART Design: Sample Size Estimation for Determining the Best Dynamic Treatment Regime

William J. Artman, Inbal Nahum-Shani, Tianshuang Wu +2

Sequential, multiple assignment, randomized trial (SMART) designs have become increasingly popular in the field of precision medicine by providing a means for comparing sequences o…