Description Usage Arguments Author(s) References Examples
Compute a Wald test given an L
vector or matrix of numeric contrasts. Requires that the
model information matrix be computed (including SE = TRUE
when using the EM method). Use
wald(model)
to observe how the information matrix columns are named, especially if
the estimated model contains constrained parameters (e.g., 1PL).
1 |
object |
estimated object from |
L |
a coefficient matrix with dimensions nconstrasts x npars. Omitting this value will return the column names of the information matrix used to identify the (potentially constrained) parameters |
C |
a constant vector of population parameters to be compared along side L, where
|
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ## Not run:
#View parnumber index
data(LSAT7)
data <- expand.table(LSAT7)
mod <- mirt(data, 1, SE = TRUE)
coef(mod)
# see how the information matrix relates to estimated parameters, and how it lines up
# with the parameter index
(infonames <- wald(mod))
index <- mod2values(mod)
index[index$est, ]
#second item slope equal to 0?
L <- matrix(0, 1, 10)
L[1,3] <- 1
wald(mod, L)
#simultaneously test equal factor slopes for item 1 and 2, and 4 and 5
L <- matrix(0, 2, 10)
L[1,1] <- L[2, 7] <- 1
L[1,3] <- L[2, 9] <- -1
L
wald(mod, L)
#logLiklihood tests (requires estimating a new model)
cmodel <- 'theta = 1-5
CONSTRAIN = (1,2, a1), (4,5, a1)'
mod2 <- mirt(data, cmodel)
#or, eqivalently
#mod2 <- mirt(data, 1, constrain = list(c(1,5), c(13,17)))
anova(mod2, mod)
## End(Not run)
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