alrt: Function to compute asymptotic likelihood ratio test of two...

In msme: Functions and Datasets for "Methods of Statistical Model Estimation"

Description

This function computes the asymptotic likelihood ratio test of two models by comparing twice the different in the log-likelihoods of the models with the Chi-squared distribution with degrees of freedom equal to the difference in the degrees of freedom of the models.

Usage

alrt(x1, x2, boundary = FALSE)

Arguments

x1	A fitted model as an object that logLik will work for.
x2	A fitted model as an object that logLik will work for.
boundary	A flag that reports whether a boundary correction should be made.

Value

out.tab	A data frame that summarizes the test.
jll.diff	The difference between the log-likelihoods.
df.diff	The difference between the degrees of freedom.
p.value	The p-value of the statistical test of the null hypothesis that there is no difference between the fit of the models.

Note

The function does not provide any checks for nesting, data equivalence, etc.

Author(s)

Andrew Robinson and Joe Hilbe.

References

Hilbe, J.M., and Robinson, A.P. 2013. Methods of Statistical Model Estimation. Chapman & Hall / CRC.

See Also

ml_glm, ml_glm2

Examples

data(medpar)

ml.poi.1 <- ml_glm(los ~ hmo + white,
                   family = "poisson",
                   link = "log",
                   data = medpar)

ml.poi.2 <- ml_glm(los ~ hmo,
                   family = "poisson",
                   link = "log",
                   data = medpar)

alrt(ml.poi.1, ml.poi.2)

msme documentation built on May 2, 2019, 5:07 a.m.