title: Tom Ten Have's contributions to causal inference and biostatistics: review and future research directions.
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.
authors.affiliation: Department of Statistics, The Wharton School, University of Pennsylvania, 400 Huntsman Hall, Philadelphia, PA 19104, U.S.A.
authors.forename: Dylan S
authors.initials: DS
authors.lastname: Small
authors.forename: Marshall M
authors.initials: MM
authors.lastname: Joffe
authors.forename: Kevin G
authors.initials: KG
authors.lastname: Lynch
authors.forename: Jason A
authors.initials: JA
authors.lastname: Roy
authors.forename: A
authors.initials: A
authors.lastname: Russell Localio
mesh_terms: D056808:Biostatistics / Q000379:methods*; D015984:Causality; D006801:Humans; D008137:Longitudinal Studies; D010349:Patient Compliance; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012044:Regression Analysis; D012106:Research