rundif: runs ordinal logistic regression DIF

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/rundif.R

Description

Runs ordinal logistic regression DIF

Usage

1
rundif(item, resp, theta, gr, criterion, alpha, beta.change, pseudo.R2, R2.change, wt)

Arguments

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

wt

optional sample weights

Details

The argument item lists the column numbers of the data frame resp to be included in the analysis.

Value

Returns a list of the following components:

stats

a data frame containing output statistics

flag

a logical vector of DIF flags

Author(s)

Seung W. Choi <[email protected]>

References

Choi, S. W., Gibbons, L. E., Crane, P. K. (2011). lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations. Journal of Statistical Software, 39(8), 1-30. URL http://www.jstatsoft.org/v39/i08/.

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.

See Also

runolr, lordif

Examples

1
## Not run: rundif(item,resp,theta,gr)

Example output

Loading required package: mirt
Loading required package: stats4
Loading required package: lattice
Loading required package: rms
Loading required package: Hmisc
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2

Attaching package: 'Hmisc'

The following objects are masked from 'package:base':

    format.pval, units

Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

lordif documentation built on May 30, 2017, 5:24 a.m.