Package: qbaconfound 0.0.0.9000

qbaconfound: Monte Carlo Quantitative Bias Analysis for Unmeasured Confounding

A flexible Monte Carlo quantitative bias analysis (QBA) for unmeasured confounding in observational studies, as described in Hughes et al. The substantive analysis may be a generalised linear model or a Cox proportional hazards model with a binary, continuous, or categorical exposure and measured confounders. The method allows for one or more binary or continuous unmeasured confounders that may be correlated with the measured confounders. Informative priors for a small number of bias parameters encode external information about the unmeasured confounders.

Authors:Tom Palmer [aut, cre], Emily Kawabata [aut], Rachael Hughes [aut]