inst/tinytest/test-exponentiate.R

In modelsummary: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready

source("helpers.R")
requiet("broom")


fit <- glm(am ~ mpg + factor(cyl), data = mtcars, family = binomial)
tid <- tidy(fit, conf.int = TRUE)

# exponentiate is a flag
expect_error(modelsummary(fit, exponentiate = "yes"))
expect_error(modelplot(fit, exponentiate = "yes"))

# logit coefficients exponentiate

tab <- modelsummary(fit, gof_omit = ".*", estimate = "estimate", statistic = NULL, output = "dataframe", exponentiate = TRUE)
x <- c("0.000", "1.448", "2.078", "2.017")
expect_equivalent(tab[[4]], x)
tab <- modelsummary(fit, gof_omit = ".*", estimate = "estimate", statistic = NULL, output = "dataframe", exponentiate = TRUE)

tab <- modelsummary(fit, gof_omit = ".*", estimate = "conf.low", statistic = NULL, output = "dataframe", exponentiate = TRUE)
x <- c("0.000", "1.026", "0.130", "0.044")
expect_equivalent(tab[[4]], x)

tab <- modelsummary(fit, gof_omit = ".*", estimate = "conf.high", statistic = NULL, output = "dataframe", exponentiate = TRUE)
expect_equivalent(tab[[4]], sprintf("%.3f", exp(tid$conf.high)))

tab <- modelsummary(fit, gof_omit = ".*", estimate = "std.error", statistic = NULL, output = "dataframe", exponentiate = TRUE)
expect_equivalent(tab[[4]], sprintf("%.3f", exp(tid$estimate) * tid$std.error))

# vcov
requiet("sandwich")
b <- coef(fit)
se <- sqrt(diag(vcovCL(fit, ~cyl)))
x <- c("0.000", "1.448", "2.078", "2.017")
tab <- modelsummary(fit,
    vcov = ~cyl, gof_omit = ".*", estimate = "estimate",
    statistic = NULL, output = "dataframe",
    exponentiate = TRUE)
expect_equivalent(tab[[4]], x)
tab <- modelsummary(fit,
    vcov = ~cyl, gof_omit = ".*", estimate = "std.error",
    statistic = NULL, output = "dataframe",
    exponentiate = TRUE)

# not sure why this no longer works. My results seem to match parameters::parameters()
expect_equivalent(tab[[4]], sprintf("%.3f", exp(b) * se))

# exponentiate vector
mod <- glm(am ~ mpg, family = binomial, data = mtcars)
mod <- list(mod, mod)
b <- coef(mod[[1]])
se <- sqrt(diag(stats::vcov(mod[[1]])))

# coefficients
tab <- modelsummary(mod,
    exponentiate = FALSE,
    output = "data.frame", statistic = NULL, fmt = identity)
expect_equivalent(b, as.numeric(tab[["(1)"]][1:2]), ignore_attr = TRUE)
expect_equivalent(b, as.numeric(tab[["(2)"]][1:2]), ignore_attr = TRUE)

tab <- modelsummary(mod,
    exponentiate = TRUE,
    output = "data.frame", statistic = NULL, fmt = identity)
expect_equivalent(exp(b), as.numeric(tab[["(1)"]][1:2]), ignore_attr = TRUE)
expect_equivalent(exp(b), as.numeric(tab[["(2)"]][1:2]), ignore_attr = TRUE)

# standard error
tab <- modelsummary(mod,
    exponentiate = TRUE, output = "data.frame",
    estimate = "std.error", statistic = NULL, fmt = identity)
expect_equivalent(exp(b) * se, as.numeric(tab[["(1)"]][1:2]), ignore_attr = TRUE)
expect_equivalent(exp(b) * se, as.numeric(tab[["(2)"]][1:2]), ignore_attr = TRUE)

# vector
tab <- modelsummary(mod,
    exponentiate = c(TRUE, FALSE),
    output = "data.frame", statistic = NULL, fmt = identity)
expect_equivalent(exp(b), as.numeric(tab[["(1)"]][1:2]), ignore_attr = TRUE)
expect_equivalent(b, as.numeric(tab[["(2)"]][1:2]), ignore_attr = TRUE)