Menu Close

Inverse Probability Weighted Estimators of Vaccine Effects Accommodating Partial Interference and Censoring

Citation

Chakladar, Sujatro; Rosin, Samuel; Hudgens, Michael G.; Halloran, M. Elizabeth; Clemens, John D.; Ali, Mohammad; & Emch, Michael E. (Online ahead of print). Inverse Probability Weighted Estimators of Vaccine Effects Accommodating Partial Interference and Censoring. Biometrics.

Abstract

Estimating population-level effects of a vaccine is challenging because there may be interference, i.e., the outcome of one individual may depend on the vaccination status of another individual. Partial interference occurs when individuals can be partitioned into groups such that interference occurs only within groups. In the absence of interference, inverse probability weighted (IPW) estimators are commonly used to draw inference about causal effects of an exposure or treatment. Tchetgen Tchetgen and VanderWeele (2012) proposed a modified IPW estimator for causal effects in the presence of partial interference. Motivated by a cholera vaccine study in Bangladesh, this paper considers an extension of the Tchetgen Tchetgen and VanderWeele IPW estimator to the setting where the outcome is subject to right censoring using inverse probability of censoring weights (IPCW). Censoring weights are estimated using proportional hazards frailty models. The large sample properties of the IPCW estimators are derived, and simulation studies are presented demonstrating the estimators' performance in finite samples. The methods are then used to analyze data from the cholera vaccine study.

URL

https://doi.org/10.1111/biom.13459

Reference Type

Journal Article

Article Type

Regular

Year Published

Online ahead of print

Journal Title

Biometrics

Author(s)

Chakladar, Sujatro
Rosin, Samuel
Hudgens, Michael G.
Halloran, M. Elizabeth
Clemens, John D.
Ali, Mohammad
Emch, Michael E.