Literature DB >> 23255088

Tom Ten Have's contributions to causal inference and biostatistics: review and future research directions.

Dylan S Small1, Marshall M Joffe, Kevin G Lynch, Jason A Roy, A Russell Localio.   

Abstract

Tom Ten Have made many contributions to causal inference and biostatistics before his untimely death. This paper reviews Tom's contributions and discusses potential related future research directions. We focus on Tom's contributions to longitudinal/repeated measures categorical data analysis and particularly his contributions to causal inference. Tom's work on causal inference was primarily in the areas of estimating the effect of receiving treatment in randomized trials with nonadherence and mediation analysis. A related area to mediation analysis he was working on at the time of his death was posttreatment effect modification with applications to designing adaptive treatment strategies.
Copyright © 2012 John Wiley & Sons, Ltd.

Entities:  

Keywords:  categorical data analysis; causal inference; longitudinal data analysis; mediation analysis; nonadherence

Mesh:

Year:  2012        PMID: 23255088     DOI: 10.1002/sim.5708

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  2 in total

1.  Using a monotone single-index model to stabilize the propensity score in missing data problems and causal inference.

Authors:  Jing Qin; Tao Yu; Pengfei Li; Hao Liu; Baojiang Chen
Journal:  Stat Med       Date:  2018-11-22       Impact factor: 2.373

2.  A brief adherence intervention that improved glycemic control: mediation by patterns of adherence.

Authors:  Heather F de Vries McClintock; Knashawn H Morales; Dylan S Small; Hillary R Bogner
Journal:  J Behav Med       Date:  2014-06-10
  2 in total

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