R: Likelihood Ratio Test for Model Comparisons and...
anova-logLik
R Documentation
Likelihood Ratio Test for Model Comparisons and Log-Likelihood Value
Description
The anova function compares two models estimated of class tam,
tam.mml or tam.mml.3pl using a likelihood ratio test.
The logLik function extracts the value of the log-Likelihood.
The function can be applied for values of tam.mml,
tam.mml.2pl, tam.mml.mfr, tam.fa,
tam.mml.3pl, tam.latreg or tamaan.
Usage
## S3 method for class 'tam'
anova(object, ...)
## S3 method for class 'tam'
logLik(object, ...)
## S3 method for class 'tam.mml'
anova(object, ...)
## S3 method for class 'tam.mml'
logLik(object, ...)
## S3 method for class 'tam.mml.3pl'
anova(object, ...)
## S3 method for class 'tam.mml.3pl'
logLik(object, ...)
## S3 method for class 'tamaan'
anova(object, ...)
## S3 method for class 'tamaan'
logLik(object, ...)
## S3 method for class 'tam.latreg'
anova(object, ...)
## S3 method for class 'tam.latreg'
logLik(object, ...)
Arguments
object
Object of class tam, tam.mml,
tam.mml.3pl, tam.latreg
or tamaan. Note that for anova two objects
(fitted models) must be provided.
...
Further arguments to be passed
Value
A data frame containing the likelihood ratio test statistic and
information criteria.
Examples
#############################################################################
# EXAMPLE 1: Dichotomous data sim.rasch - 1PL vs. 2PL model
#############################################################################
data(data.sim.rasch)
# 1PL estimation
mod1 <- tam.mml(resp=data.sim.rasch)
logLik(mod1)
# 2PL estimation
mod2 <- tam.mml.2pl(resp=data.sim.rasch , irtmodel="2PL")
logLik(mod2)
# Model comparison
anova( mod1 , mod2 )
## Model loglike Deviance Npars AIC BIC Chisq df p
## 1 mod1 -42077.88 84155.77 41 84278.77 84467.40 54.05078 39 0.05508
## 2 mod2 -42050.86 84101.72 80 84341.72 84709.79 NA NA NA
## Not run:
#############################################################################
# EXAMPLE 2: Dataset reading (sirt package): 1- vs. 2-dimensional model
#############################################################################
data(data.read,package="sirt")
# 1-dimensional model
mod1 <- tam.mml.2pl(resp= data.read )
# 2-dimensional model
mod2 <- tam.fa(resp= data.read , irtmodel="efa" , nfactors=2 ,
control=list(maxiter=150) )
# Model comparison
anova( mod1 , mod2 )
## Model loglike Deviance Npars AIC BIC Chisq df p
## 1 mod1 -1954.888 3909.777 24 3957.777 4048.809 76.66491 11 0
## 2 mod2 -1916.556 3833.112 35 3903.112 4035.867 NA NA NA
## End(Not run)