mirt (version 1.35.1)

anova-method: Compare nested models with likelihood-based statistics

Description

Compare nested models using likelihood ratio test (X2), Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Sample-Size Adjusted BIC (SABIC), and Hannan-Quinn (HQ) Criterion. When given a sequence of objects, anova tests the models against one another in the order specified.

Usage

# S4 method for SingleGroupClass
anova(object, object2, ..., bounded = FALSE, mix = 0.5, verbose = TRUE)

Arguments

object

an object of class SingleGroupClass, MultipleGroupClass, or MixedClass

object2

a second model estimated from any of the mirt package estimation methods

...

additional model objects to be sequentially compared

bounded

logical; are the two models comparing a bounded parameter (e.g., comparing a single 2PL and 3PL model with 1 df)? If TRUE then a 50:50 mix of chi-squared distributions is used to obtain the p-value

mix

proportion of chi-squared mixtures. Default is 0.5

verbose

logical; print additional information to console?

Value

a data.frame/mirt_df object

References

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. 10.18637/jss.v048.i06

Examples

# NOT RUN {
# }
# NOT RUN {
x <- mirt(Science, 1)
x2 <- mirt(Science, 2)
anova(x, x2)

# compare three models sequentially
x2 <- mirt(Science, 1, 'gpcm')
x3 <- mirt(Science, 1, 'nominal')
anova(x, x2, x3)

# in isolation
anova(x)

# with priors on first model
model <- "Theta = 1-4
          PRIOR = (1-4, a1, lnorm, 0, 10)"
xp <- mirt(Science, model)
anova(xp, x2)
anova(xp)

# bounded parameter
dat <- expand.table(LSAT7)
mod <- mirt(dat, 1)
mod2 <- mirt(dat, 1, itemtype = c(rep('2PL', 4), '3PL'))
anova(mod, mod2) #unbounded test
anova(mod, mod2, bounded = TRUE) #bounded

# priors
model <- 'F = 1-5
          PRIOR = (5, g, norm, -1, 1)'
mod1b <- mirt(dat, model, itemtype = c(rep('2PL', 4), '3PL'))
anova(mod1b)

model2 <- 'F = 1-5
          PRIOR = (1-5, g, norm, -1, 1)'
mod2b <- mirt(dat, model2, itemtype = '3PL')
anova(mod1b, mod2b)

# }