multilevel (version 2.6)

ad.m: Average deviation around mean or median

Description

This function calculates the average deviation of the mean or median as a measure of within-group agreement as proposed by Burke, Finkelstein and Dusig (1999). A basic rule for interpreting whether or not the results display practically significant levels of agreement is whether the AD value is smaller than A/6 where A represents the number of response options. For instance, A would be 5 on a five-point response option format of strongly disagree, disagree, neither, agree, strongly agree (see Dunlap, Burke & Smith-Crowe, 2003). To estimate statistical significance see the ad.m.sim function and help files.

Usage

ad.m(x, grpid, type="mean")

Arguments

x

A vector representing a single item or a matrix representing a scale of interest. If a matrix, each column of the matrix represents a scale item, and each row represents an individual respondent.

grpid

A vector identifying the groups from which x originated.

type

A character string for either the mean or median.

Value

grpid

The group identifier

AD.M

The average deviation around the mean or median for each group

gsize

Group size

References

Burke, M. J., Finkelstein, L. M., & Dusig, M. S. (1999). On average deviation indices for estimating interrater agreement. Organizational Research Methods, 2, 49-68.

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.

See Also

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

Examples

# NOT RUN {
data(bhr2000)

#Examples for multiple item scales
AD.VAL<-ad.m(bhr2000[,2:12],bhr2000$GRP)
AD.VAL[1:5,]
summary(AD.VAL)
summary(ad.m(bhr2000[,2:12],bhr2000$GRP,type="median"))

#Example for single item measure
summary(ad.m(bhr2000$HRS,bhr2000$GRP))
# }