sim.icc | R Documentation |
ICC(1) values play an important role influencing the form of relationships among variables in nested data. This simulation allows one to create data with known ICC(1) values. Multiple variables can be created both with and without level-1 correlation.
sim.icc(gsize, ngrp, icc1, nitems=1, item.cor=FALSE)
gsize |
The simulated group size. |
ngrp |
The simulated number of groups. |
icc1 |
The simulated ICC(1) value. |
nitems |
The number of items (vectors) to simulate. |
item.cor |
An option to create level-1 correlation among items. Provided as a value between 0 and 1. If used, nitems must be larger than 1. |
GRP |
The grouping designator. |
VAR1 |
The simulated value. Multiple numbered columns if nitems>1 |
Paul Bliese pdbliese@gmail.com
Bliese, P. D. (2000). Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis. In K. J. Klein & S. W. Kozlowski (Eds.), Multilevel Theory, Research, and Methods in Organizations (pp. 349-381). San Francisco, CA: Jossey-Bass, Inc.
Bliese, P. D., Maltarich, M. A., Hendricks, J. L., Hofmann, D. A., & Adler, A. B. (2019). Improving the measurement of group-level constructs by optimizing between-group differentiation. Journal of Applied Psychology, 104, 293-302.
ICC1
sim.mlcor
## Not run: set.seed(1535324) ICC.SIM<-sim.icc(gsize=10,ngrp=100,icc1=.15) ICC1(aov(VAR1~as.factor(GRP), ICC.SIM)) # 4 items with no level-1 correlation set.seed(15324) #items with no level-1 (within) correlation ICC.SIM<-sim.icc(gsize=10,ngrp=100,icc1=.15,nitems=4) mult.icc(ICC.SIM[,2:5],ICC.SIM$GRP) with(ICC.SIM,waba(VAR1,VAR2,GRP))$Cov.Theorem #Examine CorrW # 4 items with a level-1 (within) correlation of .30 set.seed(15324) ICC.SIM<-sim.icc(gsize=10,ngrp=100,icc1=.15,nitems=4, item.cor=.3) mult.icc(ICC.SIM[,2:5],ICC.SIM$GRP) with(ICC.SIM,waba(VAR1,VAR2,GRP))$Cov.Theorem #Examine CorrW ## End(Not run)
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