40.3 Omitted Variable Bias Quantification
To quantify the bias needed to change the substantive conclusion from a causal inference study.
library(konfound)
pkonfound(
est_eff = 5,
std_err = 2,
n_obs = 1000,
n_covariates = 5
)
#> Robustness of Inference to Replacement (RIR):
#> To invalidate an inference, 21.506 % of the estimate would have to be due to bias.
#> This is based on a threshold of 3.925 for statistical significance (alpha = 0.05).
#>
#> To invalidate an inference, 215 observations would have to be replaced with cases
#> for which the effect is 0 (RIR = 215).
#>
#> See Frank et al. (2013) for a description of the method.
#>
#> Citation: Frank, K.A., Maroulis, S., Duong, M., and Kelcey, B. (2013).
#> What would it take to change an inference?
#> Using Rubin's causal model to interpret the
#> robustness of causal inferences.
#> Education, Evaluation and
#> Policy Analysis, 35 437-460.
pkonfound(
est_eff = 5,
std_err = 2,
n_obs = 1000,
n_covariates = 5,
to_return = "thresh_plot"
)
