rundif {lordif} | R Documentation |
Runs ordinal logistic regression DIF
rundif(item, resp, theta, gr, criterion, alpha, beta.change, pseudo.R2, R2.change)
item |
a selection of items to be analyzed |
resp |
a data frame containing item responses |
theta |
a conditioning (matching) variable |
gr |
a vector of group identifiers |
criterion |
criterion for flagging (i.e., "CHISQR", "R2", or "BETA") |
alpha |
significance level for Chi-squared criterion |
beta.change |
proportional change for Beta criterion |
pseudo.R2 |
pseudo R-squared measure (i.e., "McFadden", "Nagelkerke", or "CoxSnell") |
R2.change |
R-squared change for pseudo R-squared criterion |
The argument item lists the column numbers of the data frame resp to be included in the analysis.
Returns a list of the following components:
stats |
a data frame containing output statistics |
flag |
a logical vector of DIF flags |
Seung W. Choi <s-choi@northwestern.edu>
Choi, S. W., Gibbons, L. E., & Crane, P. K. (under review). Development of an iterative hybrid ordinal logistic regression/IRT DIF: A Monte Carlo simulation approach for determining cutoff values. Behavior Research Methods.
Crane, P. K., Gibbons, L. E., Jolley, L., and van Belle, G. (2006). Differential item functioning analysis with ordinal logistic regression techniques: DIF detect and difwithpar. Medical Care, 44(11 Suppl 3), S115-S123.
## ## Not run: rundif(item,resp,theta,gr)