selected working papers
Bruns-Smith D, Dukes O, Feller A, Ogburn EL. Augmented balancing weights as undersmoothed regressions. Under review.
Gilbert B, Datta A, Casey J, Ogburn EL. A causal inference framework for spatial confounding. Under review.
Gilbert B, Ogburn EL, Datta A. Consistency of common spatial estimators under spatial confounding. Under review.
Srinivasan R, Bhattacharya R, Nabi R, Ogburn EL, Shpitser I. Graphical models of entangled missingness. Under review.
Nguyen TQ, Stuart EA, Scharfstein DO, Ogburn EL. Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects. Under review.
Gilbert B, Datta A, Casey J, Ogburn EL. A causal inference framework for spatial confounding. Under review.
Gilbert B, Ogburn EL, Datta A. Consistency of common spatial estimators under spatial confounding. Under review.
Srinivasan R, Bhattacharya R, Nabi R, Ogburn EL, Shpitser I. Graphical models of entangled missingness. Under review.
Nguyen TQ, Stuart EA, Scharfstein DO, Ogburn EL. Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects. Under review.
selected publications
Ogburn EL, Sofrygin O, Diaz I, and van der Laan MJ (in press). Causal inference for social network data. JASA.
Miao W, Hu W, Ogburn EL, Zhou X (in press). Identifying effects of multiple treatments in the presence of unmeasured confounding. JASA.
Ogburn EL, Shpitser I, Tchetgen Tchetgen EJ (2020). Counterexamples to "Blessings of Multiple Causes" by Wang and Blei.
Ogburn EL, Shpitser I, Tchetgen Tchetgen EJ (2019). Comment on "Blessings of Multiple Causes," with rejoinder. JASA.
Lee Y, Ogburn EL (2020). Network Dependence Can Lead to Spurious Associations and Invalid Inference. JASA.
Ogburn EL, Rudolph KE, Morello-Frosch R, Khan A, Casey JA (In press). A warning about using predictions from regression models for epidemiologic inquiry. American Journal of Epidemiology. R code for simulations here. https://doi.org/10.1093/aje/kwaa282
Ogburn EL, Bierer BE, Brookmeyer R, et al. Aggregating data from COVID-19 trials. Science.
Ogburn EL, Shpitser I, Lee Y (2020). Causal inference, social networks, and chain graphs. JRSS-A.
Nguyen TQ, Dafoe A, Ogburn EL (2018). Collider bias in binary variable structures. Epidemiologic Methods.
Ogburn EL. Challenges to estimating contagion effects from observational data. Published here.
Ogburn EL and VanderWeele TJ (2017). Vaccines, contagion, and social networks. Annals of Applied Statistics.
Ogburn EL and VanderWeele TJ (2014). Causal diagrams for interference. Statistical Science.
Ogburn EL, Rotnizky A, Robins JM (2014). Doubly robust estimation of the local average treatment effect curve. Journal of the Royal Statistical Society, Series B. Appendix.
Ogburn EL, VanderWeele TJ (2012). Bias attenuation results for nondifferentially mismeasured ordinal and coarsened confounders. Biometrika. (supplementary material)
Ogburn EL, VanderWeele TJ (2012). Analytic Results on the Bias Due to Nondifferential Misclassification of a Binary Mediator. American Journal of Epidemiology.
Ogburn EL, VanderWeele TJ (2012). On the nondifferential misclassification of a binary confounder.Epidemiology 23: 433-439.
Miao W, Hu W, Ogburn EL, Zhou X (in press). Identifying effects of multiple treatments in the presence of unmeasured confounding. JASA.
Ogburn EL, Shpitser I, Tchetgen Tchetgen EJ (2020). Counterexamples to "Blessings of Multiple Causes" by Wang and Blei.
Ogburn EL, Shpitser I, Tchetgen Tchetgen EJ (2019). Comment on "Blessings of Multiple Causes," with rejoinder. JASA.
Lee Y, Ogburn EL (2020). Network Dependence Can Lead to Spurious Associations and Invalid Inference. JASA.
Ogburn EL, Rudolph KE, Morello-Frosch R, Khan A, Casey JA (In press). A warning about using predictions from regression models for epidemiologic inquiry. American Journal of Epidemiology. R code for simulations here. https://doi.org/10.1093/aje/kwaa282
Ogburn EL, Bierer BE, Brookmeyer R, et al. Aggregating data from COVID-19 trials. Science.
Ogburn EL, Shpitser I, Lee Y (2020). Causal inference, social networks, and chain graphs. JRSS-A.
Nguyen TQ, Dafoe A, Ogburn EL (2018). Collider bias in binary variable structures. Epidemiologic Methods.
Ogburn EL. Challenges to estimating contagion effects from observational data. Published here.
Ogburn EL and VanderWeele TJ (2017). Vaccines, contagion, and social networks. Annals of Applied Statistics.
Ogburn EL and VanderWeele TJ (2014). Causal diagrams for interference. Statistical Science.
Ogburn EL, Rotnizky A, Robins JM (2014). Doubly robust estimation of the local average treatment effect curve. Journal of the Royal Statistical Society, Series B. Appendix.
Ogburn EL, VanderWeele TJ (2012). Bias attenuation results for nondifferentially mismeasured ordinal and coarsened confounders. Biometrika. (supplementary material)
Ogburn EL, VanderWeele TJ (2012). Analytic Results on the Bias Due to Nondifferential Misclassification of a Binary Mediator. American Journal of Epidemiology.
Ogburn EL, VanderWeele TJ (2012). On the nondifferential misclassification of a binary confounder.Epidemiology 23: 433-439.
