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

Description Usage Arguments Value Author(s) References See Also Examples

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

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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

Author(s)

Paul Bliese paul.bliese@moore.sc.edu

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.

See Also

ICC1

Examples

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 ## 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)
ICC.SIM<-sim.icc(gsize=10,ngrp=100,icc1=.15,nitems=4) #items with no level-1 correlation
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 correlation of .30
set.seed(15324)
ICC.SIM<-sim.icc(gsize=10,ngrp=100,icc1=.15,nitems=4, item.cor=.3) #.30 level-1 item correlations
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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