sim.icc: Simulate 2-level ICC(1) values with and without level-1 correlation

Description

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.

Usage

sim.icc(gsize, ngrp, icc1, nitems=1, item.cor=FALSE)

Arguments

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.

Value

GRP

The grouping designator.

VAR1

The simulated value. Multiple numbered columns if nitems>1

References

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.

Examples

Run this code

# NOT RUN {
 
# }
# 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 
# }