View source: R/TIRTfit-methods.R
gof.TIRTfit | R Documentation |
By default lavaan will return a value for degrees of freedom that ignores redundancies amongst the estimated model thresholds. This function corrects the degrees of freedom, and then recalculates the associated chi-square test statistic p-value and root mean square error of approximation (RMSEA).
## S3 method for class 'TIRTfit'
gof(object, ...)
gof(object, ...)
object |
A |
... |
currently unused. |
Note this function is currently only implemented for lavaan.
A vector containing the chi-square value, adjusted degrees of freedom, p-value, and RMSEA.
# load the data
data("triplets")
# define the blocks of items
blocks <-
set_block(c("i1", "i2", "i3"), traits = c("t1", "t2", "t3"),
signs = c(1, 1, 1)) +
set_block(c("i4", "i5", "i6"), traits = c("t1", "t2", "t3"),
signs = c(-1, 1, 1)) +
set_block(c("i7", "i8", "i9"), traits = c("t1", "t2", "t3"),
signs = c(1, 1, -1)) +
set_block(c("i10", "i11", "i12"), traits = c("t1", "t2", "t3"),
signs = c(1, -1, 1))
# generate the data to be understood by 'thurstonianIRT'
triplets_long <- make_TIRT_data(
data = triplets, blocks = blocks, direction = "larger",
format = "pairwise", family = "bernoulli", range = c(0, 1)
)
# fit the data using lavaan
fit <- fit_TIRT_lavaan(triplets_long)
gof(fit)
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