rwg.sim: Simulate rwg values from a random null distribution

In multilevel: Multilevel Functions

Simulate rwg values from a random null distribution

Description

Based on the work of Dunlap, Burke and Smith-Crowe (2003). Draws data from a random uniform null distribution, and calculates the within group agreement measure rwg for single item measures as described in James, Demaree and& Wolf (1984). By repeatedly drawing random samples, a null distribution of the rwg is generated. The null sampling distribution can be used to calculate confidence intervals for different combinations of group sizes and number of response options (A).

Usage

rwg.sim(gsize, nresp, nrep)

Arguments

gsize	Group size upon which to base the rwg simulation.
nresp	The number of response options (e.g., there would be 5 response options if using Strongly Disagree, Disagree, Neither, Agree, Strongly Agree).
nrep	The number of rwg values to simulate. This will generally be 10,000 or more, although the examples use nrep of 500 to reduce computational demands.

Value

rwg	rwg value from each simulation.
gsize	Group size used in the rwg simulation.
nresp	Simulated number of response options.
nitems	Will always be 1 for an rwg estimate.
rwg.95	Estimated 95 percent confidence interval. Values greater than or equal to rwg.95 are considered significant, p<.05.

Author(s)

Paul Bliese [e-mail]

References

Cohen, A., Doveh, E., & Eick, U. (2001). Statistical properties of the rwg(j) index of agreement. Psychological Methods, 6, 297-310.

Dunlap, W. P., Burke, M. J., & Smith-Crowe, K. (2003). Accurate tests of statistical significance for rwg and average deviation interrater agreement indices. Journal of Applied Psychology, 88, 356-362.

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.

See Also

ad.m awg rwg.j rwg rwg.j.sim rgr.agree

Examples

#An example from Dunlap et al. (2003).  The estimate from Dunlap
#et al. Table 2 is 0.53 (p=.05)
RWG.OUT<-rwg.sim(gsize=10,nresp=5,nrep=500)
summary(RWG.OUT)
quantile(RWG.OUT, c(.95,.99))

multilevel documentation built on March 18, 2022, 5:47 p.m.