runolr: runs ordinal logistic regression models

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

View source: R/runolr.R

Description

Runs ordinal logistic regression models and produces DIF statistics and effect size measures

Usage

1
runolr(rv, ev, gr, wt)

Arguments

rv

a response variable

ev

an explanatory variable (e.g., conditioning variable)

gr

a vector of group identifiers

wt

a vector of optional sample weights

Details

Model 1: ev

Model 2: ev + gr

Model 3: ev*gr or equivalently ev + gr + ev*gr

Value

Returns a list of the following components:

chi12

prob for the LR Chi-square comparing Model 1 vs. Model 2

chi13

prob for the LR Chi-square comparing Model 1 vs. Model 3

chi23

prob for the LR Chi-square comparing Model 2 vs. Model 3

beta12

proportional change in the coefficient for ev

pseudo1.CoxSnell

Cox & Snell psudo R-square for Model 1

pseudo2.CoxSnell

Cox & Snell psudo R-square for Model 2

pseudo3.CoxSnell

Cox & Snell psudo R-square for Model 1

pseudo1.Nagelkerke

Nagelkerke psudo R-square for Model 1

pseudo2.Nagelkerke

Nagelkerke psudo R-square for Model 2

pseudo3.Nagelkerke

Nagelkerke psudo R-square for Model 3

pseudo1.McFadden

McFadden psudo R-square for Model 1

pseudo2.McFadden

McFadden psudo R-square for Model 2

pseudo3.McFadden

McFadden psudo R-square for Model 3

pseudo12.CoxSnell

Cox & Snell R-square change from Model 1 to Model 2

pseudo13.CoxSnell

Cox & Snell R-square change from Model 1 to Model 3

pseudo23.CoxSnell

Cox & Snell R-square change from Model 2 to Model 3

pseudo12.Nagelkerke

Nagelkerke R-square change from Model 1 to Model 2

pseudo13.Nagelkerke

Nagelkerke R-square change from Model 1 to Model 3

pseudo23.Nagelkerke

Nagelkerke R-square change from Model 2 to Model 3

pseudo12.McFadden

McFadden R-square change from Model 1 to Model 2

pseudo13.McFadden

McFadden R-square change from Model 1 to Model 3

pseudo23.McFadden

McFadden R-square change from Model 2 to Model 3

df12

df for the LR Chi-square comparing Model 1 and Model 2

df13

df for the LR Chi-square comparing Model 1 and Model 3

df23

df for the LR Chi-square comparing Model 2 and Model 3

Author(s)

Seung W. Choi <choi.phd@gmail.com>

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., & 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

rundif, lordif, rms

Examples

1
## Not run: runolr(rv, ev, 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, round.POSIXt, trunc.POSIXt, units

Loading required package: SparseM

Attaching package: 'SparseM'

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

    backsolve

lordif documentation built on May 2, 2019, 2:13 p.m.