| check.errors {mokken} | R Documentation |
Check the number of Guttman errors (Gplus) and the number of infrequent scores (Oplus) for each respondent
Description
Returns a lost containing outlier scores Gplus (number of Guttman errors; Guttman, 1944) and Oplus for each respondent (Zijlstra, van der Ark & Sijtsma, 2007).
Usage
check.errors(X, returnGplus = TRUE, returnOplus = FALSE)
Arguments
X |
matrix or data frame of numeric data
containing the responses of |
returnGplus |
Boolean. If |
returnOplus |
Boolean. If |
Value
List. Depending on the values of returnGplus and returnOplus, the output contains outlier score Gplus (the number of Guttman errors)
and Oplusfor each respondent
Author(s)
L. A. van der Ark L.A.vanderArk@uva.nl
References
Guttman, L. (1944) A basis for scaling qualitative data. American Sociological Review, 9, 139-150.
Meijer, R. R. (1994) The number of Guttman errors as a simple and powerful person-fit statistic. Applied Psychological Measurement, 18, 311-314. doi:10.1177/014662169401800402
Mokken, R. J. (1971) A Theory and Procedure of Scale Analysis. De Gruyter.
Molenaar, I.W., & Sijtsma, K. (2000) User's Manual MSP5 for Windows [Software manual]. IEC ProGAMMA.
Sijtsma, K., & Molenaar, I. W. (2002) Introduction to nonparametric item response theory. Sage.
Van der Ark, L. A. (2007). Mokken scale analysis in R. Journal of Statistical Software. doi:10.18637/jss.v020.i11
Zijlstra, W. P., Van der Ark, L. A., & Sijtsma, K. (e2007). Outlier detection in test and questionnaire data. Multivariate Behavioral Research, 42, 531-555. doi:10.1080/00273170701384340
See Also
check.ca,
check.iio,
check.monotonicity,
check.pmatrix,
check.reliability
coefH,
plot.restscore.class,
summary.restscore.class
Examples
data(acl)
Communality <- acl[,1:10]
Gplus <- check.errors(Communality, TRUE, FALSE)$Gplus
Oplus <- check.errors(Communality, FALSE, TRUE)$Oplus
hist(Gplus, breaks = 0:max(Gplus))