q3 {pairwise} | R Documentation |
Q3 Fit Statistic
Description
Calculation of Q3 fit statistic for the rasch model based on the residuals, which was proposed by Yen (1984).
Usage
q3(
pers_obj,
na_treat = 0,
use = "complete.obs",
res = "stdr",
method = "pearson"
)
Arguments
pers_obj |
an object of class |
na_treat |
value to be assigned to residual cells which have missing data in the original response matrix. default is set to |
use |
a character string as used in function |
res |
a character string defining which type of (rasch–) residual to analyze when computing the correlations. This must be (exactly) one of the strings "sr" for score residuals , "stdr" for standardised residuals, "srsq" for score residuals squared, or "stdrsq" for standardised residuals squared. The default is set to |
method |
a character string as used in function |
Details
The lower level letter 'q' was used (intead of 'Q') for naming the function because the name 'Q3' was already used in another IRT package – namly TAM
. As perhaps some users like to use both packages simultaniously, an alternative naming convention was choosen for 'pairwise'. No other details in the moment.
Value
An object of class c("Q3","list")
.
References
Yen, W. M. (1984). Effects of Local Item Dependence on the Fit and Equating Performance of the Three-Parameter Logistic Model. Applied Psychological Measurement, 8(2), 125–145. https://doi.org/10.1177/014662168400800201
Examples
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data(bfiN) # loading reponse data
pers_obj <- pers(pair(bfiN))
result <- q3(pers_obj)
str(result) # to see whats in ;-)
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