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sjstats (version 0.7.1)

deff: Design effects for two-level mixed models

Description

Compute the design effect (also called Variance Inflation Factor) for mixed models with two-level design.

Usage

deff(n, icc = 0.05)

Arguments

n
Average number of observations per grouping cluster (i.e. level-2 unit).
icc
Assumed intraclass correlation coefficient for multilevel-model.

Value

The design effect (Variance Inflation Factor) for the two-level model.

Details

The formula for the design effect is simply (1 + (n - 1) * icc).

References

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: 239–257. \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("#1")}10.1177/0163278703255230http://doi.org/10.1177/0163278703255230doi:\ifelse{latex}{\out{~}}{ }latex~ 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. \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("#1")}10.1002/0470013192.bsa492http://doi.org/10.1002/0470013192.bsa492doi:\ifelse{latex}{\out{~}}{ }latex~ 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):235–40. \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("#1")}10.1370/afm.1347http://doi.org/10.1370/afm.1347doi:\ifelse{latex}{\out{~}}{ }latex~ 10.1370/afm.1347

Examples

Run this code
# Design effect for two-level model with 30 cluster groups
# and an assumed intraclass correlation coefficient of 0.05.
deff(n = 30)

# Design effect for two-level model with 24 cluster groups
# and an assumed intraclass correlation coefficient of 0.2.
deff(n = 24, icc = 0.2)

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