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personpar(object, ...)
"personpar"(object, ref = NULL, vcov = TRUE, interval = NULL, tol = 1e-8, ...)
"personpar"(object, ref = NULL, vcov = TRUE, interval = NULL, tol = 1e-8, ...)
"personpar"(object, ref = NULL, vcov = TRUE, interval = NULL, tol = 1e-8, ...)
NULL
(the default), all items are used
(sum zero restriction). This argument will passed over to
internal calls of itempar
.uniroot
to search for the person parameter estimates.uniroot
.optim
in case of vcov = TRUE
.personpar
and additional attributes "model"
(the model
name), and "vcov"
(the covariance matrix of the estimates if
vcov = TRUE
or an NA-matrix otherwise).
personpar
is both, a class to represent person parameters
of item response models as well as a generic function. The generic
function can be used to estimate the person parameters of a given item
response model. Person parameters are estimated via uniroot()
with
the estimation equations given by Hoijtink & Boomsma (1995) as well
as Andersen (1995). This approach is fast and estimates for all
possible raw scores are available. If the covariance matrix of the
estimated person parameters is requested (vcov = TRUE
), an
additional call of optim
is necessary to obtain the Hessian.
With this approach, person parameters are available only for observed
raw scores.
For objects of class personpar
, several methods to standard
generic functions exist: print
, coef
, vcov
.
coef
and vcov
can be used to extract the
person parameters and covariance matrix without additional
attributes. Based on this Wald tests or confidence intervals can be
easily computed, e.g., via confint
.
Herbert Hoijtink, and Anne Boomsma. On Person Parameter Estimation in the Dichotomous Rasch Model. In Gerhard H. Fischer, and Ivo W. Molenaar, (1995). Rasch Models: Foundations, Recent Developments, and Applications.
itempar
, threshpar
,
discrpar
o <- options(digits = 4)
## load verbal aggression data
data("VerbalAggression", package = "psychotools")
## fit a Rasch model to dichotomized verbal aggression data and
ram <- raschmodel(VerbalAggression$resp2)
## extract person parameters
rap <- personpar(ram)
rap
## extract variance-covariance matrix and standard errors
vc <- vcov(rap)
sqrt(diag(vc))
## Wald confidence intervals
confint(rap)
## person parameters for RSM/PCM fitted to original polytomous data
rsm <- rsmodel(VerbalAggression$resp)
pcm <- pcmodel(VerbalAggression$resp)
cbind(personpar(rsm, vcov = FALSE), personpar(pcm, vcov = FALSE))
options(digits = o$digits)
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