Lagrange test for freeing parameters
Lagrange (i.e., score) test to test whether parameters should be freed from a more constrained baseline model.
lagrange(mod, parnum, SE.type = "Oakes", type = "Richardson", ...)
mod |
an estimated model |
parnum |
a vector, or list of vectors, containing one or more parameter
locations/sets of locations to be tested.
See objects returned from |
SE.type |
type of information matrix estimator to use. See |
type |
type of numerical algorithm passed to |
... |
additional arguments to pass to |
Phil Chalmers rphilip.chalmers@gmail.com
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi: 10.18637/jss.v048.i06
## Not run:
dat <- expand.table(LSAT7)
mod <- mirt(dat, 1, 'Rasch')
(values <- mod2values(mod))
#test all fixed slopes individually
parnum <- values$parnum[values$name == 'a1']
lagrange(mod, parnum)
# compare to LR test for first two slopes
mod2 <- mirt(dat, 'F = 1-5
FREE = (1, a1)', 'Rasch')
coef(mod2, simplify=TRUE)$items
anova(mod, mod2)
mod2 <- mirt(dat, 'F = 1-5
FREE = (2, a1)', 'Rasch')
coef(mod2, simplify=TRUE)$items
anova(mod, mod2)
mod2 <- mirt(dat, 'F = 1-5
FREE = (3, a1)', 'Rasch')
coef(mod2, simplify=TRUE)$items
anova(mod, mod2)
# test slopes first two slopes and last three slopes jointly
lagrange(mod, list(parnum[1:2], parnum[3:5]))
# test all 5 slopes and first + last jointly
lagrange(mod, list(parnum[1:5], parnum[c(1, 5)]))
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