reghelper (version 0.3.3)

beta.glm: Standardized coeffients of a model.

Description

beta.glm returns the summary of a linear model where all variables have been standardized.

Usage

# S3 method for glm
beta(model, x = TRUE, y = FALSE, skip = NULL, ...)

Arguments

model

A fitted generalized linear model of type 'glm'.

x

Logical. Whether or not to standardize predictor variables.

y

Logical. Whether or not to standardize criterion variables.

skip

A string vector indicating any variables you do not wish to be standarized.

...

Not currently implemented; used to ensure consistency with S3 generic.

Value

Returns the summary of a generalized linear model, with the output showing the beta coefficients, standard error, t-values, and p-values for each predictor.

Details

This function takes a generalized linear regression model and standardizes the variables, in order to produce standardized (i.e., beta) coefficients rather than unstandardized (i.e., B) coefficients.

Note: Unlike beta.lm, the y parameter is set to FALSE by default, to avoid issues with some family functions (e.g., binomial).

See Also

beta.glm

Examples

# NOT RUN {
# mtcars data
model1 <- glm(vs ~ wt + hp, data=mtcars, family='binomial')
beta(model1)  # wt and hp standardized, vs is not by default
# }