rwg.j.lindell {multilevel}

Lindell et al. r*wg(j) agreement index for multi-item scales

Description

Calculates the Lindell et al r*wg(j) within-group agreement index for multiple item measures. The r*wg(j) is similar to the James, Demaree and Wolf (1984) rwg and rwg(j) indices. The r*wg(j) index is calculated by taking the average item variability as the Observed Group Variance, and using the average item variability in the numerator of the rwg formula (rwg=1-(Observed Group Variance/ Expected Random Variance)). In practice, this means that the r*wg(j) does not increase as the number of items in the scale increases as does the rwg(j). Additionally, the r*wg(j) allows Observed Group Variances to be larger than Expected Random Variances. In practice this means that r*wg(j) values can be negative.

Usage

rwg.j.lindell(x, grpid, ranvar=2)

Arguments

x

A matrix representing the scale of interest upon which one is interested in estimating agreement. Each column of the matrix represents a separate scale item, and each row represents an individual respondent.

grpid

A vector identifying the groups from which x originated.

ranvar

The random variance to which actual group variances are compared. The value of 2 represents the variance from a rectangular distribution in the case where there are 5 response options (e.g., Strongly Disagree, Disagree, Neither, Agree, Strongly Agree). In cases where there are not 5 response options, the rectangular distribution is estimated using the formula \mathtt{ranvar}=(A^{2}-1)/12 where A is the number of response options. Note that one is not limited to the rectangular distribution; rather, one can include any appropriate random value for ranvar.

Value

grpid

The group identifier

rwg.lindell

The r*wg(j) estimate for the group

gsize

The group size

Author(s)

Paul Bliese [e-mail]

References

James, L.R., Demaree, R.G., & Wolf, G. (1984). Estimating within-group interrater reliability with and without response bias. Journal of Applied Psychology, 69, 85-98.

Lindell, M. K. & Brandt, C. J. (1999). Assessing interrater agreement on the job relevance of a test: A comparison of CVI, T, rWG(J), and r*WG(J) indexes. Journal of Applied Psychology, 84, 640-647.

See Also

ad.m awg rwg rwg.j rgr.agree

Examples

data(lq2002)
RWGOUT<-rwg.j.lindell(lq2002[,3:13],lq2002$COMPID)
RWGOUT[1:10,]
summary(RWGOUT)