| 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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