Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses
Internal function used to calculate arbitrary bias factors.
Plot bias factor as function of confounding relative risks
Sensitivity analysis for unmeasured confounding in meta-analyses
Unmeasured confounding
Convert an effect measure
Internal function used to fit roots of a polynomial made up of the pro...
Declare an effect measure
Compute an E-value for unmeasured confounding
Compute E-value for a hazard ratio and its confidence interval limits
Compute an E-value for unmeasured confounding for an additive interact...
Compute E-value for a difference of means and its confidence interval ...
Compute E-value for a linear regression coefficient estimate
Compute E-value for an odds ratio and its confidence interval limits
Compute E-value for a population-standardized risk difference and its ...
Compute E-value for a risk ratio or rate ratio and its confidence inte...
Misclassification
Create a set of biases for a multi-bias sensitivity analysis
Calculate a bound for the bias
Calculate a multiple-bias E-value
Selection bias
Compute selection bias E-value for a hazard ratio and its confidence i...
Plots for sensitivity analyses
Compute selection bias E-value for an estimate and its confidence inte...
Compute selection bias E-value for an odds ratio and its confidence in...
Compute selection bias E-value for a risk ratio or rate ratio and its ...
Compute E-value for single value of risk ratio
Compute selection bias E-value for single value of risk ratio as well ...
Estimate risk ratio and compute CI limits from two-by-two table
Conducts sensitivity analyses for unmeasured confounding, selection bias, and measurement error (individually or in combination; VanderWeele & Ding (2017) <doi:10.7326/M16-2607>; Smith & VanderWeele (2019) <doi:10.1097/EDE.0000000000001032>; VanderWeele & Li (2019) <doi:10.1093/aje/kwz133>; Smith & VanderWeele (2021) <arXiv:2005.02908>). Also conducts sensitivity analyses for unmeasured confounding in meta-analyses (Mathur & VanderWeele (2020a) <doi:10.1080/01621459.2018.1529598>; Mathur & VanderWeele (2020b) <doi:10.1097/EDE.0000000000001180>) and for additive measures of effect modification (Mathur et al., under review).