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sjstats (version 0.2.0)

deff: Design effects for two-level mixed models

Description

Compute the design effect 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 for the two-level model.

References

  • 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

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)

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