profilelike.glm: Profile Likelihood for Generalized Linear Models

In ProfileLikelihood: Profile Likelihood for a Parameter in Commonly Used Statistical Models

Profile Likelihood for Generalized Linear Models

Description

This function provides values for a profile likelihood and a normalized profile likelihood for a parameter of interest in a generalized linear model.

Usage

profilelike.glm(formula, data, profile.theta, family = stats::gaussian, 
	offset.glm = NULL, lo.theta = NULL, hi.theta = NULL, length = 300, 
	round = 2, subset = NULL, weights = NULL, offset = NULL, ...)

Arguments

formula	see corresponding documentation in glm.
data	a data frame. See corresponding documentation in glm.
profile.theta	a parameter of interest, theta; must be a numeric variable.
family	see corresponding documentation in glm.
offset.glm	same usage as offset in glm. See corresponding documentation for offset in glm.
lo.theta	lower bound for a parameter of interest to obtain values for a profile likelihood.
hi.theta	upper bound for a parameter of interest to obtain values for a profile likelihood.
length	length of numerical grid values for a parameter of interest to obtain values for a profile likelihood.
round	the number of decimal places for round function to automatically define lower and upper bounds of numerical grid for a parameter of interest. If an automatically defined parameter range is not appropriate, increase the number or specify lo.theta and hi.theta.
subset	should not be provided.
weights	should not be provided.
offset	should not be provided. Instead use offset.glm.
...	further arguments passed to or from other methods.

Details

This function provides values for a profile likelihood and a normalized profile likelihood for a parameter of interest in a generalized linear model. Users must define a parameter of interest in a generalized linear model. This function can be used for generalized linear models comparable with the glm function. However, arguments weights, subset, and offset should not be provided. An argument offset in glm function can be provided using offset.glm. A normalized profile likelihood is obtained by a profile likelihood being divided by the maximum value of the profile likelihood so that a normalized profile likelihood ranges from 0 to 1.

Value

theta	numerical grid values for a parameter of interest in a specified range (between lower and upper bounds).
profile.lik	numerical values for a profile likelihood corresponding to theta in a specified range (between lower and upper bounds).
profile.lik.norm	numerical values for a normalized profile likelihood ranging from 0 to 1.

Warning

Arguments weights, subset, and offset in the glm function are not comparable.

Missing values should be removed.

Author(s)

Leena Choi <[e-mail]>

See Also

profilelike.plot, profilelike.summary, profilelike.lm, profilelike.polr, profilelike.gls, profilelike.lme, glm

Examples

data(dataglm)
xx <- profilelike.glm(y ~ x1 + x2, data=dataglm, profile.theta="group", 
				family=binomial(link="logit"), length=500, round=2)
profilelike.plot(theta=xx$theta, profile.lik.norm=xx$profile.lik.norm, round=2)

ProfileLikelihood documentation built on Aug. 25, 2023, 5:15 p.m.