gof_demo_grouped: Grouped-covariate companion to 'gof_demo' (replicated...

In ebrahim.gof: Goodness-of-Fit and Calibration Tests for Logistic Regression

Grouped-covariate companion to gof_demo (replicated covariate patterns)

Description

A companion dataset to gof_demo built from the same data-generating process and seed discipline (see data-raw/make_gof_demo.R), except that the covariates are coarsened before the linear predictor is computed: age is rounded to 10-year bins (20, 30, ..., 70) and bmi to whole integers. The recorded covariates are therefore exactly the covariates the outcome was generated from, and many observations share a covariate pattern (328 distinct patterns among 800 observations, versus one pattern per observation in gof_demo).

Usage

gof_demo_grouped

Format

A data frame with 800 rows and 5 variables:

outcome

binary response, 0/1 (event rate about 0.27).

age

age in years, rounded to 10-year bins (20, 30, ..., 70). The true model depends on (binned) age quadratically.

bmi

body mass index in kg/m^2, rounded to whole integers.

sex

binary covariate, 0 = female, 1 = male.

treatment

binary covariate, 0 = control, 1 = treated.

Details

Its purpose is to demonstrate the sparse-versus-grouped distinction that run.all.gof surfaces: the battery reports the per-observation ("sparse") and per-covariate-pattern ("grouped") forms of the pattern-sensitive tests (Pearson, deviance, McCullagh) side by side, and on replicated-pattern data such as this the two forms can disagree on the same fitted model. On the all-continuous gof_demo (every observation its own pattern) the two forms coincide – the degenerate case.

The true data-generating linear predictor has the same form as for gof_demo,

\eta = -0.6 + 0.8 z_a - 0.7 z_a^2 + 0.5 z_b + 0.4\,\mathrm{sex} - 0.3\,\mathrm{treatment},

with z_a = (\mathrm{age} - 45)/14 and z_b = (\mathrm{bmi} - 27)/4 computed from the binned age and bmi, and \Pr(\mathrm{outcome} = 1) = \mathrm{plogis}(\eta).

Source

Simulated; see data-raw/make_gof_demo.R in the package sources.

See Also

gof_demo, run.all.gof

Examples

data("gof_demo_grouped", package = "ebrahim.gof")
fit <- glm(outcome ~ age + bmi + sex + treatment,
           data = gof_demo_grouped, family = binomial)
# sparse and grouped forms reported side by side:
run.all.gof(fit, include_slow = FALSE, install = "no")

ebrahim.gof documentation built on Oct. 11, 2026, 5:07 p.m.