tipr (version 0.4.0)

r_value: Robustness value

Description

This function wraps the sensemakr::robustness_value() function

Usage

r_value(effect, se, df, ...)

Arguments

effect

Numeric. Observed exposure - outcome effect from a regression model. This is the point estimate (beta coefficient)

se

Numeric. Standard error of the effect in the previous parameter.

df

Numeric positive value. Residual degrees of freedom for the model used to estimate the observed exposure - outcome effect. This is the total number of observations minus the number of parameters estimated in your model. Often for models estimated with an intercept this is N - k - 1 where k is the number of predictors in the model.

...

Optional arguments passed to the sensemakr::robustness_value() function.

Value

Numeric. Robustness value

References

Carlos Cinelli, Jeremy Ferwerda and Chad Hazlett (2021). sensemakr: Sensitivity Analysis Tools for Regression Models. R package version 0.1.4. https://CRAN.R-project.org/package=sensemakr

Examples

# NOT RUN {
r_value(0.5, 0.1, 102)
# }