glm.work: Define a Generalized Linear Model

In MultiRobust: Multiply Robust Methods for Missing Data Problems

Description

Define a generalized linear model. All the arguments in glm are allowed except for data. Supported types of family include gaussian, binomial, poisson, Gamma and inverse.gaussian.

Usage

glm.work(formula, family = gaussian, weights = NULL, ...)

Arguments

formula	The formula of the model to be fitted.
family	The distribution of the response variable and the link function to be used in the model.
weights	The prior weights to be used in the model.
...	Addition arguments for the function glm.

See Also

glm.

Examples

# A logistic regression with response R and covariates X1 and X2
mis1 <- glm.work(formula = R ~ X1 + X2, family = binomial(link = logit))

MultiRobust documentation built on June 4, 2019, 1:03 a.m.