bruceR (version 0.7.2)

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

Description

Tidy report of GLM (lm and glm models).

Usage

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

Arguments

model

A model fitted by lm or glm function.

robust

[only for lm and glm] FALSE (default), TRUE (then the default is "HC1"), "HC0", "HC1", "HC2", "HC3", "HC4", "HC4m", or "HC5". It will add a table with heteroskedasticity-robust standard errors (aka. Huber-White standard errors). For details, see ?sandwich::vcovHC and ?jtools::summ.lm.

*** "HC1" is the default of Stata, whereas "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. If you specify cluster, you may also specify the type of robust. If you do not specify robust, "HC1" will be set as default.

digits, nsmall

Number of decimal places of output. Default is 3.

...

Other parameters. You may re-define formula, data, or family.

Value

No return value.

See Also

HLM_summary, regress

Examples

# NOT RUN {
## 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")
# }