Tyler J Vander Weele

Summary

Affiliation: Harvard University
Country: USA

Publications

  1. doi request reprint The use of propensity score methods in psychiatric research
    Tyler VanderWeele
    Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    Int J Methods Psychiatr Res 15:95-103. 2006
  2. doi request reprint On the distinction between interaction and effect modification
    Tyler J VanderWeele
    Department of Epidemiology and Biostatistics, Harvard University, Boston, MA 02115, USA
    Epidemiology 20:863-71. 2009
  3. pmc Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 22:42-52. 2011
  4. doi request reprint A mapping between interactions and interference: implications for vaccine trials
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 23:285-92. 2012
  5. pmc Environmental confounding in gene-environment interaction studies
    Tyler J VanderWeele
    Am J Epidemiol 178:144-52. 2013
  6. pmc Medically induced preterm birth and the associations between prenatal care and infant mortality
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard University, Boston, MA 02115, USA
    Ann Epidemiol 23:435-40. 2013
  7. pmc Factors influencing the decision to participate in medical premarital examinations in Hubei Province, Mid-China
    Peigang Wang
    School of Public Health, Wuhan University, Wuhan 430071, China
    BMC Public Health 13:217. 2013
  8. pmc A three-way decomposition of a total effect into direct, indirect, and interactive effects
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 24:224-32. 2013
  9. doi request reprint Inference for influence over multiple degrees of separation on a social network
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA, U S A
    Stat Med 32:591-6; discussion 597-9. 2013
  10. pmc On the reciprocal association between loneliness and subjective well-being
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA
    Am J Epidemiol 176:777-84. 2012

Research Grants

  1. Theory and methods for sufficient cause interactions
    Tyler VanderWeele; Fiscal Year: 2010

Detail Information

Publications37

  1. doi request reprint The use of propensity score methods in psychiatric research
    Tyler VanderWeele
    Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    Int J Methods Psychiatr Res 15:95-103. 2006
    ..An introduction to propensity score methods is given and a series of examples illustrating their use in psychiatric research is presented...
  2. doi request reprint On the distinction between interaction and effect modification
    Tyler J VanderWeele
    Department of Epidemiology and Biostatistics, Harvard University, Boston, MA 02115, USA
    Epidemiology 20:863-71. 2009
    ..A characterization is given of the settings in which interaction and effect modification coincide...
  3. pmc Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 22:42-52. 2011
    ..The bias formulas are particularly simple and easy to use in settings in which the unmeasured confounding variable is binary with constant effect on the outcome across treatment levels...
  4. doi request reprint A mapping between interactions and interference: implications for vaccine trials
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 23:285-92. 2012
    ..We discuss the implications of this correspondence for our conceptualizations of interaction and for application to vaccine trials and many other settings in which spillover effects may be present...
  5. pmc Environmental confounding in gene-environment interaction studies
    Tyler J VanderWeele
    Am J Epidemiol 178:144-52. 2013
    ..We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies. ..
  6. pmc Medically induced preterm birth and the associations between prenatal care and infant mortality
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard University, Boston, MA 02115, USA
    Ann Epidemiol 23:435-40. 2013
    ..We hypothesized that prenatal care may lead to lower infant mortality in part by increasing the detection of obstetrical problems for which the clinical response may be to medically induce preterm birth...
  7. pmc Factors influencing the decision to participate in medical premarital examinations in Hubei Province, Mid-China
    Peigang Wang
    School of Public Health, Wuhan University, Wuhan 430071, China
    BMC Public Health 13:217. 2013
    ..To investigate the attitudes of premarital couples towards the premarital screening program after the abolition of compulsory screening in China and to study the factors influencing participation...
  8. pmc A three-way decomposition of a total effect into direct, indirect, and interactive effects
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 24:224-32. 2013
    ..The three-way decomposition is illustrated by examples from genetic and perinatal epidemiology, and discussion is given to what is gained over the traditional two-way decomposition into a direct and an indirect effect...
  9. doi request reprint Inference for influence over multiple degrees of separation on a social network
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA, U S A
    Stat Med 32:591-6; discussion 597-9. 2013
    ..We discuss analytic procedures appropriate for assessing evidence for each possible interpretation and the increasingly difficult methodological challenges present in each interpretation...
  10. pmc On the reciprocal association between loneliness and subjective well-being
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA
    Am J Epidemiol 176:777-84. 2012
    ..Mechanisms responsible for the asymmetry are discussed. Developing interventions for loneliness and subjective well-being could have substantial psychological and health benefits...
  11. pmc Invited commentary: structural equation models and epidemiologic analysis
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    Am J Epidemiol 176:608-12. 2012
    ..In light of the strong assumptions employed by SEMs, the author argues that they should be used principally for the purposes of exploratory analysis and hypothesis generation when a broad range of effects are potentially of interest...
  12. pmc Invited commentary: assessing mechanistic interaction between coinfecting pathogens for diarrheal disease
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
    Am J Epidemiol 176:396-9. 2012
    ..is of sufficient magnitude to provide strong evidence of mechanistic interaction between rotavirus and Giardia and between rotavirus and Escherichia. coli/Shigellae, even without any assumptions about monotonicity...
  13. pmc Components of the indirect effect in vaccine trials: identification of contagion and infectiousness effects
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA02115, USA
    Epidemiology 23:751-61. 2012
    ..We also give a sensitivity analysis technique to assess how inferences would change under violations of the identification assumptions. The concepts and results of this paper are illustrated with hypothetical vaccine trial data...
  14. pmc Genetic variants on 15q25.1, smoking, and lung cancer: an assessment of mediation and interaction
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    Am J Epidemiol 175:1013-20. 2012
    ..5% and 9.2%, respectively. These analyses indicate that the association of the variants with lung cancer operates primarily through other pathways...
  15. pmc Mediation analysis with multiple versions of the mediator
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 23:454-63. 2012
    ..The results are illustrated using 2 examples from the literature, one in which the versions of the mediator are unknown and another in which the mediator itself has been dichotomized...
  16. pmc Rising preterm birth rates, 1989-2004: changing demographics or changing obstetric practice?
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    Soc Sci Med 74:196-201. 2012
    ..Further research should examine the degree to which these changes in obstetric practice affect infant morbidity and mortality...
  17. pmc Estimating measures of interaction on an additive scale for preventive exposures
    Mirjam J Knol
    Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, GA, Utrecht, The Netherlands
    Eur J Epidemiol 26:433-8. 2011
    ..23; 0.49], AP = -0.29 [95%CI: -0.98; 0.40], S = 0.43 [95%CI: 0.07; 2.60]), all indicating negative interaction. Preventive factors should not be used to calculate measures of interaction on an additive scale without recoding...
  18. pmc Conditioning on intermediates in perinatal epidemiology
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 23:1-9. 2012
    ..The various methodologic approaches described in this paper are applicable to a number of similar settings in perinatal epidemiology...
  19. pmc Bounding the infectiousness effect in vaccine trials
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 22:686-93. 2011
    ..This applies to bias from selection due to the persons in the comparison, and also to selection due to pathogen virulence. We illustrate our results with an example from the literature...
  20. pmc Inference for causal interactions for continuous exposures under dichotomization
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, Massachusetts 02115, USA
    Biometrics 67:1414-21. 2011
    ..The results in this article are applied to a study of the interactive effects between smoking and arsenic exposure from well water in producing skin lesions...
  21. pmc A new criterion for confounder selection
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, Massachusetts 02115, USA
    Biometrics 67:1406-13. 2011
    ..We discuss some additional covariate selection results that preserve unconfoundedness and that may be of interest when used with our criterion...
  22. doi request reprint Concerning the consistency assumption in causal inference
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 20:880-3. 2009
    ..The use of stochastic counterfactuals can help relax what is effectively being presupposed by the treatment-variation irrelevance assumption and the consistency assumption...
  23. pmc Case-only gene-environment interaction studies: when does association imply mechanistic interaction?
    Tyler J VanderWeele
    Harvard School of Public Health, Departments of Epidemiology and Biostatistics, 677 Huntington Avenue, Boston, MA 02115, USA
    Genet Epidemiol 34:327-34. 2010
    ..We furthermore show these tests for mechanistic interaction can be extended to scenarios in which the genetic and environmental factors are negatively associated in the population rather than independent...
  24. pmc Marginal structural models for sufficient cause interactions
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Am J Epidemiol 171:506-14. 2010
    ..It is furthermore shown that marginal structural models can be used not only to test for sufficient cause interactions but also to give lower bounds on the prevalence of such sufficient cause interactions...
  25. pmc Epistatic interactions
    Tyler J VanderWeele
    Harvard University, USA
    Stat Appl Genet Mol Biol 9:Article 1. 2010
    ..These relations can sometimes be exploited to empirically test for "epistatic interactions" in the sense of the masking of the effect of a particular genetic variant by a variant at another locus...
  26. doi request reprint Bias formulas for sensitivity analysis for direct and indirect effects
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, MA 02115, USA
    Epidemiology 21:540-51. 2010
    ..The bias formulas are illustrated by examples in the literature concerning direct and indirect effects in which mediator-outcome confounding may be present...
  27. pmc Genetic self knowledge and the future of epidemiologic confounding
    Tyler J VanderWeele
    Department of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
    Am J Hum Genet 87:168-72. 2010
    ..This commentary explores the reverse question of what personalized genetic medicine might do to our research process, not only in genetics, but in epidemiology more generally...
  28. pmc Tests for compositional epistasis under single interaction-parameter models
    Tyler J VanderWeele
    Harvard School of Public Health Departments of Epidemiology and Biostatistics, Boston, Massachusetts 02115, United States
    Ann Hum Genet 75:146-56. 2011
    ..We describe the implications of these tests for cohort, case-control, case-only and family-based study designs and we illustrate the methods using an example of gene-gene interaction already reported in the literature...
  29. pmc Odds ratios for mediation analysis for a dichotomous outcome
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    Am J Epidemiol 172:1339-48. 2010
    ..The approach presented here, however, will apply even when there are interactions between the effect of the exposure and the mediator on the outcome...
  30. pmc Interpretation of subgroup analyses in randomized trials: heterogeneity versus secondary interventions
    Tyler J VanderWeele
    Harvard School of Public Health, Boston, Massachusetts 02115, USA
    Ann Intern Med 154:680-3. 2011
    ..The authors demonstrate this point by using examples from published randomized trials...
  31. pmc Causal interactions in the proportional hazards model
    Tyler J VanderWeele
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Epidemiology 22:713-7. 2011
    ..The results are illustrated by hypothetical and data analysis examples...
  32. pmc Remarks on antagonism
    Tyler J VanderWeele
    Departments of Epidemiology and Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    Am J Epidemiol 173:1140-7. 2011
    ..The results in this paper are illustrated by application to examples drawn from the existing literature on gene-gene and gene-environment interactions...
  33. pmc A marginal structural model analysis for loneliness: implications for intervention trials and clinical practice
    Tyler J VanderWeele
    Harvard University, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    J Consult Clin Psychol 79:225-35. 2011
    ..We use longitudinal data on loneliness and depressive symptoms and a new class of causal models to illustrate how empirical evidence can be used to inform intervention trial design and clinical practice...
  34. doi request reprint Principal interactions analysis for repeated measures data: application to gene-gene and gene-environment interactions
    Bhramar Mukherjee
    Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
    Stat Med 31:2531-51. 2012
    ..We carry out simulation studies under an array of classical interaction models and common epistasis models to illustrate the properties of the principal interactions analysis procedure in comparison with the classical alternatives...
  35. pmc Efficient designs of gene-environment interaction studies: implications of Hardy-Weinberg equilibrium and gene-environment independence
    Jinbo Chen
    Department of Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA 19104, USA
    Stat Med 31:2516-30. 2012
    ..In addition, supplementing external control data to an existing case-control sample leads to improved power for assessing effects of G or E in the presence of G-E interactions...
  36. pmc Attributable fractions for sufficient cause interactions
    Tyler J VanderWeele
    Harvard University, Boston, MA, USA
    Int J Biostat 6:Article 5. 2010
    ..2006) are discussed and compared. A method is described to estimate the lower bounds on attributable fractions using marginal structural models. Identification is discussed in settings in which time-dependent confounding may be present...

Research Grants1

  1. Theory and methods for sufficient cause interactions
    Tyler VanderWeele; Fiscal Year: 2010
    ..The research will make important advances to the statistical literature on the concept of interaction and on the implications of measurement error for causal inference. ..