GLM_summary: Tidy report of GLM ('lm' and 'glm' models).

In bruceR: Broadly Useful Convenient and Efficient R Functions

Tidy report of GLM (lm and glm models).

Description

NOTE: model_summary() is preferred.

Usage

GLM_summary(model, robust = FALSE, cluster = NULL, digits = 3, ...)

Arguments

model	A model fitted with lm or glm function.
robust	[Only for lm and glm] Robust standard errors. Add a table with heteroskedasticity-robust standard errors (aka. Huber-White standard errors). Options: FALSE (default), TRUE ("HC1"), "HC0", "HC1", "HC2", "HC3", "HC4", "HC4m", "HC5". For details, see sandwich::vcovHC() and jtools::summ.lm(). Note: "HC1" is the default of Stata, while "HC3" is the default suggested by the sandwich package.
cluster	[Only for lm and glm] Cluster-robust standard errors are computed if cluster is set to the name of the input data's cluster variable or is a vector of clusters.
digits	Number of decimal places of output. Defaults to 3.
...	Other arguments. You may re-define formula, data, or family.

Value

No return value.

See Also

print_table() (print simple table)

model_summary() (strongly suggested)

HLM_summary()

regress()

Examples

## Example 1: OLS regression
lm = lm(Temp ~ Month + Day + Wind + Solar.R, data=airquality)
GLM_summary(lm)
GLM_summary(lm, robust="HC1")
# Stata's default is "HC1"
# R package <sandwich>'s default is "HC3"

## Example 2: Logistic regression
glm = glm(case ~ age + parity + education + spontaneous + induced,
          data=infert, family=binomial)
GLM_summary(glm)
GLM_summary(glm, robust="HC1", cluster="stratum")

bruceR documentation built on Aug. 21, 2025, 5:38 p.m.