anova.tam.Rd
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
.
# S3 method for tam anova(object, ...) # S3 method for tam logLik(object, ...) # S3 method for tam.mml anova(object, ...) # S3 method for tam.mml logLik(object, ...) # S3 method for tam.mml.3pl anova(object, ...) # S3 method for tam.mml.3pl logLik(object, ...) # S3 method for tamaan anova(object, ...) # S3 method for tamaan logLik(object, ...) # S3 method for tam.latreg anova(object, ...) # S3 method for tam.latreg logLik(object, ...) # S3 method for tam.np anova(object, ...) # S3 method for tam.np logLik(object, ...)
object | Object of class |
---|---|
... | Further arguments to be passed |
A data frame containing the likelihood ratio test statistic and information criteria.
############################################################################# # EXAMPLE 1: Dichotomous data sim.rasch - 1PL vs. 2PL model ############################################################################# data(data.sim.rasch) # 1PL estimation mod1 <- TAM::tam.mml(resp=data.sim.rasch) logLik(mod1) # 2PL estimation mod2 <- TAM::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 if (FALSE) { ############################################################################# # EXAMPLE 2: Dataset reading (sirt package): 1- vs. 2-dimensional model ############################################################################# data(data.read, package="sirt") # 1-dimensional model mod1 <- TAM::tam.mml.2pl(resp=data.read ) # 2-dimensional model mod2 <- TAM::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 }