tipr (version 1.0.1)

tip_or_with_binary: Tip an observed odds ratio with a binary confounder.

Description

Choose two of the following three to specify, and the third will be estimated:

• exposed_confounder_prev

• unexposed_confounder_prev

• confounder_outcome_effect

Alternatively, specify all three and the function will return the number of unmeasured confounders specified needed to tip the analysis.

Usage

tip_or_with_binary(
  effect_observed,
  exposed_confounder_prev = NULL,
  unexposed_confounder_prev = NULL,
  confounder_outcome_effect = NULL,
  verbose = TRUE,
  or_correction = FALSE
)

Value

Data frame.

Arguments

effect_observed

Numeric positive value. Observed exposure - outcome odds ratio. This can be the point estimate, lower confidence bound, or upper confidence bound.

exposed_confounder_prev

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

unexposed_confounder_prev

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

confounder_outcome_effect

Numeric positive value. Estimated relationship between the unmeasured confounder and the outcome

verbose

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

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 TRUE. Default: FALSE.

Examples

tip_or_with_binary(0.9, 0.9, 0.1)