Confidence intervals for logistic regression coefficients — confint.logistic

Confidence intervals for the coefficients B (log-odds scale) of a logistic_regression model.

The default method = "wald" gives Wald intervals (\(B \pm z_{1-\alpha/2} \cdot SE\)), the interval SPSS LOGISTIC REGRESSION reports as "95\ summary() prints: exp(confint(model)) reproduces the Lower/Upper columns of the coefficients table. method = "profile" gives the profile-likelihood intervals of stats::confint() for glm objects.

Usage

# S3 method for class 'logistic_regression'
confint(object, parm, level = 0.95, method = c("wald", "profile"), ...)

Arguments

object: A logistic_regression result (ungrouped).
parm: Coefficients to compute intervals for (names or indices; default all).
level: Confidence level (default 0.95).
method: "wald" (default, SPSS) or "profile".
...: Passed to the underlying confint method.

Value

A matrix with one row per coefficient and columns for the lower and upper limits (log-odds scale).

Examples

survey_data$high_satisfaction <- as.integer(survey_data$life_satisfaction >= 4)
model <- logistic_regression(survey_data, high_satisfaction ~ age + gender)
confint(model)        # Wald (SPSS)
#>                     2.5 %    97.5 %
#> (Intercept)   0.043750737 0.5762897
#> age          -0.006071836 0.0034194
#> genderFemale -0.032012673 0.2909808
exp(confint(model))   # SPSS "95% C.I. for EXP(B)"
#>                  2.5 %   97.5 %
#> (Intercept)  1.0447219 1.779424
#> age          0.9939466 1.003425
#> genderFemale 0.9684943 1.337739