Thomas R. Ten Have
Affiliations: | University of Pennsylvania, Philadelphia, PA, United States |
Area:
Biostatistics BiologyGoogle:
"Thomas Ten Have"Children
Sign in to add trainee| A. R. Localio | grad student | 2005 | Penn |
| Lingfeng Yang | grad student | 2007 | Penn |
| Seunghee Baek | grad student | 2010 | Penn |
| Bing Cai | grad student | 2010 | Penn |
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Publications
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| Faerber JA, Joffe MM, Small DS, et al. (2017) A Simple Model Allowing Modification of the Effect of a Randomized Intervention by Post-Randomization Variables Journal of Causal Inference. 5 |
| Bellamy SL, Baek S, Troxel AB, et al. (2016) A copula approach to estimate reliability: An application to self-reported sexual behaviors among HIV serodiscordant couples Statistics and Its Interface. 9: 57-67 |
| Cai B, Hennessy S, Flory JH, et al. (2012) Simulation study of instrumental variable approaches with an application to a study of the antidiabetic effect of bezafibrate. Pharmacoepidemiology and Drug Safety. 21: 114-20 |
| Ten Have TR, Joffe MM. (2012) A review of causal estimation of effects in mediation analyses. Statistical Methods in Medical Research. 21: 77-107 |
| Almirall D, Ten Have T, Murphy SA. (2010) Structural nested mean models for assessing time-varying effect moderation. Biometrics. 66: 131-9 |
| Gallop R, Small DS, Lin JY, et al. (2009) Mediation analysis with principal stratification. Statistics in Medicine. 28: 1108-30 |
| Cheng J, Small DS, Tan Z, et al. (2009) Efficient nonparametric estimation of causal effects in randomized trials with noncompliance Biometrika. 96: 19-36 |
| Lynch KG, Cary M, Gallop R, et al. (2008) Causal Mediation Analyses for Randomized Trials. Health Services & Outcomes Research Methodology. 8: 57-76 |
| Small DS, Ten Have TR, Rosenbaum PR. (2008) Randomization inference in a group-randomized trial of treatments for depression: Covariate adjustment, noncompliance, and quantile effects Journal of the American Statistical Association. 103: 271-279 |
| Bellamy SL, Lin JY, Ten Have TR. (2007) An introduction to causal modeling in clinical trials. Clinical Trials (London, England). 4: 58-73 |