Fit Generalized Linear Models with an Offset

This function is a wrapper around stats::glm() that uses a column from data as an offset.

Usage

glm_offset(
  formula,
  family = "gaussian",
  data,
  offset_col = "offset",
  weights = NULL
)

Arguments

formula

A model formula

family

A function or character string describing the link function and error distribution.

data

Optional. A data frame containing variables used in the model.

offset_col

Character string. The name of a column in data containing offsets.

weights

Optional weights to use in the fitting process.

Value

A glm object. See stats::glm() for full details.

Details

Outside of the tidymodels ecosystem, glm_offset() has no advantages over stats::glm() since that function allows for offsets to be specified in the formula interface or its offset argument.

Within tidymodels, glm_offset() provides an advantage because it will ensure that offsets are included in the data whenever resamples are created.

The formula, family, data, and weights arguments have the same meanings as stats::glm(). See that function's documentation for full details.

See also

stats::glm()

Examples

us_deaths$off <- log(us_deaths$population)
glm_offset(deaths ~ age_group + gender, family = "poisson",
           us_deaths, offset_col = "off")
#> 
#> Call:  stats::glm(formula = formula, family = family, data = data, weights = weights, 
#>     offset = offset)
#> 
#> Coefficients:
#>    (Intercept)  age_group35-44  age_group45-54  age_group55-64  age_group65-74  
#>        -6.8842          0.4426          1.2114          1.9908          2.7147  
#> age_group75-84    age_group85+      genderMale  
#>         3.6465          4.7707          0.3280  
#> 
#> Degrees of Freedom: 139 Total (i.e. Null);  132 Residual
#> Null Deviance:	    51700000 
#> Residual Deviance: 245000 	AIC: 246900