profilelike.gls: Profile Likelihood for Linear Models for Longitudinal...

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

Profile Likelihood for Linear Models for Longitudinal Responses Fitted by Generalized Least Squares

Description

This function provides values for a profile likelihood and a normalized profile likelihood for a parameter of interest in a linear model for longitudinal responses fitted by generalized least squares.

Usage

profilelike.gls(formula, data, correlation = NULL, subject, profile.theta, 
		method = "ML", lo.theta, hi.theta, length = 300, round = 2, 
		subset = NULL, weights = NULL, ...)

Arguments

formula	see corresponding documentation in gls.
data	a data frame. See corresponding documentation in gls.
correlation	see corresponding documentation in gls.
subject	see corresponding documentation in gls.
profile.theta	a parameter of interest, theta; must be a numeric variable.
method	see corresponding documentation in gls.
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.
...	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 linear model for longitudinal responses fitted by generalized least squares. Users must define a parameter of interest in the model. This function can be used for models for longitudinal responses comparable with the gls function. However, arguments weights and subset should not be provided. 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 and subset in the gls function are not comparable.

Missing values should be removed.

Author(s)

Leena Choi <[e-mail]>

See Also

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

Examples

data(Gasoline, package = "nlme")
xx <- profilelike.gls(formula=yield ~ endpoint, correlation=nlme::corAR1(form = ~ 1 | id),
	data=Gasoline, subject="Sample", profile.theta="vapor", method="ML", 
	lo.theta=1, hi.theta=5, length=500, round=2)
profilelike.plot(theta=xx$theta, profile.lik.norm=xx$profile.lik.norm, round=4)

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