Warning: Undefined array key "mm" in /www/wwwroot/www.ai-bt.com/si.php on line 10 Deprecated: trim(): Passing null to parameter #1 ($string) of type string is deprecated in /www/wwwroot/www.ai-bt.com/si.php on line 10 Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part II: proofs of results.

Literature DB >> 20405047

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part II: proofs of results.

Liliana Orellana¹, Andrea Rotnitzky, James M Robins.

Abstract

In this companion article to "Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part I: Main Content" [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the optimal index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption.

Keywords: causality; double-robust; dynamic treatment regime; inverse probability weighted; marginal structural model; optimal treatment regime

Mesh：

Year: 2010 PMID： 20405047 PMCID： PMC2854089 DOI： 10.2202/1557-4679.1242

Source DB: PubMed Journal: Int J Biostat ISSN： 1557-4679 Impact factor: 0.968

1 in total

1. Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: main content.

Authors: Liliana Orellana; Andrea Rotnitzky; James M Robins
Journal: Int J Biostat Date: 2010 Impact factor: 0.968

1 in total

26 in total

1. When to start treatment? A systematic approach to the comparison of dynamic regimes using observational data.

Authors: Lauren E Cain; James M Robins; Emilie Lanoy; Roger Logan; Dominique Costagliola; Miguel A Hernán
Journal: Int J Biostat Date: 2010 Impact factor: 0.968

2. A sequential multiple assignment randomized trial (SMART) protocol for empirically developing an adaptive preventive intervention for college student drinking reduction.

Authors: Megan E Patrick; Jeffrey A Boatman; Nicole Morrell; Anna C Wagner; Grace R Lyden; Inbal Nahum-Shani; Cheryl A King; Erin E Bonar; Christine M Lee; Mary E Larimer; David M Vock; Daniel Almirall
Journal: Contemp Clin Trials Date: 2020-07-25 Impact factor: 2.226

3. Diagnosing Covariate Balance Across Levels of Right-Censoring Before and After Application of Inverse-Probability-of-Censoring Weights.

Authors: John W Jackson
Journal: Am J Epidemiol Date: 2019-12-31 Impact factor: 4.897

4. Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research.

Authors: Daniel Almirall; Inbal Nahum-Shani; Nancy E Sherwood; Susan A Murphy
Journal: Transl Behav Med Date: 2014-09 Impact factor: 3.046

5. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available.

Authors: Miguel A Hernán; James M Robins
Journal: Am J Epidemiol Date: 2016-03-18 Impact factor: 4.897

6. Designing a pilot sequential multiple assignment randomized trial for developing an adaptive treatment strategy.

Authors: Daniel Almirall; Scott N Compton; Meredith Gunlicks-Stoessel; Naihua Duan; Susan A Murphy
Journal: Stat Med Date: 2012-03-22 Impact factor: 2.373

7. SMART: Study protocol for a sequential multiple assignment randomized controlled trial to optimize weight loss management.

Authors: Angela Fidler Pfammatter; Inbal Nahum-Shani; Margaret DeZelar; Laura Scanlan; H Gene McFadden; Juned Siddique; Donald Hedeker; Bonnie Spring
Journal: Contemp Clin Trials Date: 2019-05-23 Impact factor: 2.226