tipr (version 0.4.0)

adjust_coef_with_binary: Adjust an observed coefficient from a loglinear model with a binary confounder

Description

Adjust an observed coefficient from a loglinear model with a binary confounder

Usage

adjust_coef_with_binary(
  effect,
  exposed_p,
  unexposed_p,
  outcome_association,
  verbose = TRUE
)

Arguments

effect

Numeric. Observed exposure - outcome effect from a loglinear model. This can be the beta coefficient, the lower confidence bound of the beta coefficient, or the upper confidence bound of the beta coefficient.

exposed_p

Numeric between 0 and 1. Estimated prevalence of the unmeasured confounder in the exposed population

unexposed_p

Numeric between 0 and 1. Estimated prevalence of the unmeasured confounder in the unexposed population

outcome_association

Numeric. Estimated association between the unmeasured confounder and the outcome.

verbose

Logical. Indicates whether to print informative message. Default: TRUE

Value

Data frame.

Examples

# NOT RUN {
adjust_coef_with_binary(1.1, 0.5, 0.3, 1.3)
# }