adjust_or {tipr} | R Documentation |
Adjust an observed odds ratio for a normally distributed confounder
Description
Adjust an observed odds ratio for a normally distributed confounder
Usage
adjust_or(
effect_observed,
exposure_confounder_effect,
confounder_outcome_effect,
verbose = getOption("tipr.verbose", TRUE),
or_correction = FALSE
)
adjust_or_with_continuous(
effect_observed,
exposure_confounder_effect,
confounder_outcome_effect,
verbose = getOption("tipr.verbose", TRUE),
or_correction = FALSE
)
Arguments
effect_observed |
Numeric positive value. Observed exposure - outcome odds ratio. This can be the point estimate, lower confidence bound, or upper confidence bound. |
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: |
or_correction |
Logical. Indicates whether to use a correction factor.
The methods used for this function are based on risk ratios. For rare
outcomes, an odds ratio approximates a risk ratio. For common outcomes,
a correction factor is needed. If you have a common outcome (>15%),
set this to |
Value
Data frame.
Examples
adjust_or(1.2, 0.9, 1.3)