| mult.icc {multilevel} | R Documentation |
Multiple ICCs from a dataset
Description
Estimates ICC(1) and ICC(2) values for each column given a data frame and a group identifier. Uses a mixed-effects estimate of the ICC, so ICC values cannot be negative. In cases where ICC values are assumed to be zero or negative, the ANOVA-based formulas should be used (see the ICC1 and ICC2 functions). The mult.icc function only works with one level of nesting.
Usage
mult.icc(x, grpid)
Arguments
x |
A data frame containing the variables of interest in each column. |
grpid |
A vector identifying the groups from which the variables originated. |
Value
Variable |
The variable name. |
ICC1 |
Intraclass correlation coefficient 1. |
ICC2 |
Group mean reliability or intraclass correlation coefficient 2. |
Author(s)
Paul Bliese pdbliese@gmail.com
References
Bartko, J.J. (1976). On various intraclass correlation reliability coefficients. Psychological Bulletin, 83, 762-765.
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.
See Also
Examples
library(nlme)
data(bh1996)
mult.icc(bh1996[,c("HRS","LEAD","COHES")],grpid=bh1996$GRP)