Effect Table of a Fitted Outcome Model — effects

The tidy one-row-per-term table of estimates, confidence intervals and corrected p-values.

Usage

effects_table(
  x,
  intercept = FALSE,
  significant = FALSE,
  alpha = 0.05,
  digits = 3
)

Arguments

x: A net_outcome_model from outcome_model.
intercept: Keep the intercept row? Default FALSE.
significant: Keep only terms whose corrected p-value is below alpha? Default FALSE.
alpha: Threshold used by significant. Default 0.05.
digits: Rounding for the numeric columns. Default 3; p_value and p_adj are never rounded.

Value

A data.frame with the same columns as the model's effect table, one row per retained term. The intercept row is dropped unless intercept = TRUE, and every term is kept unless significant = TRUE restricts them to p_adj < alpha.

Examples

set.seed(1)
d <- data.frame(hint = rbinom(200, 1, 0.5))
d$success <- rbinom(200, 1, plogis(-0.3 + 0.9 * d$hint))
effects_table(outcome_model(d, outcome = "success", predictors = "hint"))
#>   term estimate std_error statistic ci_lower ci_upper      p_value        p_adj
#> 1 hint    1.522     0.305     4.994    0.925     2.12 5.910034e-07 5.910034e-07
#>   odds_ratio or_lower or_upper
#> 1      4.583    2.522     8.33