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Compute the design effect (also called Variance Inflation Factor) for mixed models with two-level design.
deff(n, icc = 0.05)
Average number of observations per grouping cluster (i.e. level-2 unit).
Assumed intraclass correlation coefficient for multilevel-model.
The design effect (Variance Inflation Factor) for the two-level model.
The formula for the design effect is simply (1 + (n - 1) * icc)
.
Bland JM. 2000. Sample size in guidelines trials. Fam Pract. (17), 17-20.
Hsieh FY, Lavori PW, Cohen HJ, Feussner JR. 2003. An Overview of Variance Inflation Factors for Sample-Size Calculation. Evaluation & the Health Professions 26: 239<U+2013>257. 10.1177/0163278703255230
Snijders TAB. 2005. Power and Sample Size in Multilevel Linear Models. In: Everitt BS, Howell DC (Hrsg.). Encyclopedia of Statistics in Behavioral Science. Chichester, UK: John Wiley & Sons, Ltd. 10.1002/0470013192.bsa492
Thompson DM, Fernald DH, Mold JW. 2012. Intraclass Correlation Coefficients Typical of Cluster-Randomized Studies: Estimates From the Robert Wood Johnson Prescription for Health Projects. The Annals of Family Medicine;10(3):235<U+2013>40. 10.1370/afm.1347
# NOT RUN {
# Design effect for two-level model with 30 observations per
# cluster group (level-2 unit) and an assumed intraclass
# correlation coefficient of 0.05.
deff(n = 30)
# Design effect for two-level model with 24 observation per cluster
# group and an assumed intraclass correlation coefficient of 0.2.
deff(n = 24, icc = 0.2)
# }
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