Extract raw coefs from model object
Return a list (or data.frame) of raw item and group level coefficients. Note that while
the output to the console is rounded to three digits, the returned list of objects is not.
Hence, elements from cfs <- coef(mod); cfs[[1]]
will contain the unrounded results (useful
for simulations).
## S4 method for signature 'SingleGroupClass' coef( object, CI = 0.95, printSE = FALSE, rotate = "none", Target = NULL, IRTpars = FALSE, rawug = FALSE, as.data.frame = FALSE, simplify = FALSE, unique = FALSE, verbose = TRUE, ... )
object |
an object of class |
CI |
the amount of converged used to compute confidence intervals; default is 95 percent confidence intervals |
printSE |
logical; print the standard errors instead of the confidence intervals? When
|
rotate |
see |
Target |
a dummy variable matrix indicting a target rotation pattern |
IRTpars |
logical; convert slope intercept parameters into traditional IRT parameters?
Only applicable to unidimensional models. If a suitable ACOV estimate was computed in the fitted
model, and |
rawug |
logical; return the untransformed internal g and u parameters?
If |
as.data.frame |
logical; convert list output to a data.frame instead? |
simplify |
logical; if all items have the same parameter names (indicating they are of the same class) then they are collapsed to a matrix, and a list of length 2 is returned containing a matrix of item parameters and group-level estimates |
unique |
return the vector of uniquely estimated parameters |
verbose |
logical; allow information to be printed to the console? |
... |
additional arguments to be passed |
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) x <- mirt(dat, 1) coef(x) coef(x, IRTpars = TRUE) coef(x, simplify = TRUE) #with computed information matrix x <- mirt(dat, 1, SE = TRUE) coef(x) coef(x, printSE = TRUE) coef(x, as.data.frame = TRUE) #two factors x2 <- mirt(Science, 2) coef(x2) coef(x2, rotate = 'varimax') ## End(Not run)
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