adjust_coef {tipr} | R Documentation |
Adjust an observed regression coefficient for a normally distributed confounder
Description
Adjust an observed regression coefficient for a normally distributed confounder
Usage
adjust_coef(
effect_observed,
exposure_confounder_effect,
confounder_outcome_effect,
verbose = getOption("tipr.verbose", TRUE)
)
adjust_coef_with_continuous(
effect_observed,
exposure_confounder_effect,
confounder_outcome_effect,
verbose = getOption("tipr.verbose", TRUE)
)
Arguments
effect_observed |
Numeric. Observed exposure - outcome effect from a regression model. This can be the beta coefficient, the lower confidence bound of the beta coefficient, or the upper confidence bound of the beta coefficient. |
exposure_confounder_effect |
Numeric. Estimated difference in scaled means between the unmeasured confounder in the exposed population and unexposed population |
confounder_outcome_effect |
Numeric. Estimated relationship between the unmeasured confounder and the outcome. |
verbose |
Logical. Indicates whether to print informative message.
Default: |
Value
Data frame.
Examples
## Update an observed coefficient of 0.5 with an unmeasured confounder
## with a difference in scaled means between exposure groups of 0.2
## and coefficient of 0.3
adjust_coef(0.5, 0.2, 0.3)
[Package tipr version 1.0.2 Index]