rgr.agree {multilevel} | R Documentation |
This function uses random group resampling (RGR) to estimate within group agreement. RGR agreement compares within group variances from actual groups to within group variances from pseudo groups. If variances on the construct of interest in the actual groups are significantly smaller than variances from pseudo groups, one can concludes that there is significant agreement.
rgr.agree(x, grpid, nrangrps)
x |
The vector representing the construct of interest. This is the variable about which one is interested in determining whether or not group members agree. |
grpid |
A vector identifying the groups from which x originated (actual group membership). |
nrangrps |
A number representing the number of random groups that one is interested in generating. Note that the number of random groups created must be directly divisible by the number of actual groups to ensure that group sizes of pseudo groups and actual groups are identical. The rgr.agree routine will generate the number of pseudo groups that most closely approximates nrangrps given the group size characteristics of one's data. |
An object of class 'rgr.agree' with the following components:
NRanGrp |
The number of random groups created. |
AvRGRVar |
The average within-group variance of the random groups. |
SDRGRVar |
The standard deviation of the random group variances used in the z-score estimate. |
zvalue |
The z-score for the difference between the actual group and random group variances. |
RGRVARS |
The random group variances. |
Paul Bliese paul.bliese@us.army.mil
Bliese, P. D., & Halverson, R. R. (2002). Using random group resampling in multilevel research. Leadership Quarterly, 13, 53-68.
Bliese, P.D., Halverson, R. R., & Rothberg, J. (2000). Using random group resampling (RGR) to estimate within-group agreement with examples using the statistical language R. Walter Reed Army Institute of Research.
data(bh1996) RGROUT<-rgr.agree(bh1996$HRS,bh1996$GRP,1000) summary(RGROUT)