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

`power.bira3r1`

calculates statistical power for designs with 3-levels
where level 1 units are randomly assigned to treatment and control groups within level 2 units (random blocks).

1 2 3 4 | ```
power.bira3r1(mdes=.25, alpha=.05, two.tail=TRUE,
rho2, rho3, omega2, omega3,
P=.50, R12=0, RT22=0, RT32=0, g3=0,
n, J, K, ...)
``` |

`mdes` |
minimum detectable effect size. |

`alpha` |
probability of type I error. |

`two.tail` |
logical; |

`rho2` |
proportion of variance in the outcome explained by level 2 units. |

`rho3` |
proportion of variance in the outcome explained by level 3 units. |

`omega2` |
treatment effect heterogeneity as ratio of treatment effect variance among level 2 units to the residual variance at level 2. |

`omega3` |
treatment effect heterogeneity as ratio of treatment effect variance among level 3 units to the residual variance at level 3. |

`P` |
average proportion of level 1 units randomly assigned to treatment within level 2 units. |

`g3` |
number of covariates at level 3. |

`R12` |
proportion of level 1 variance in the outcome explained by level 1 covariates. |

`RT22` |
proportion of treatment effect variance among level 2 units explained by level 2 covariates. |

`RT32` |
proportion of treatment effect variance among level 3 units explained by level 3 covariates. |

`n` |
harmonic mean of level 1 units across level 2 units (or simple average). |

`J` |
harmonic mean of level 2 units across level 3 units (or simple average). |

`K` |
level 3 sample size. |

`...` |
to handle extra parameters passed from other functions, do not define any additional parameters. |

Power formula was derived within power analysis framework descibed by Hedges & Rhoads (2009). Further definition of design parameters can be found in Dong & Maynard (2013).

`fun` |
function name. |

`par` |
list of parameters used in power calculation. |

`df` |
degrees of freedom |

`M` |
multiplier for MDES calcuation given degrees of freedom, |

`power` |
statistical power (1 - type II error). |

Metin Bulus [email protected] Nianbo Dong [email protected]

Dong, N., & Maynard, R. A. (2013). PowerUp!: A Tool for Calculating Minum Detectable Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-Experimental Design Studies,*Journal of Research on Educational Effectiveness, 6(1)*, 24-6.

Hedges, L. & Rhoads, C.(2009). Statistical Power Analysis in Education Research (NCSER 2010-3006). Washington, DC: National Center for Special Education Research, Institute of Education Sciences, U.S. Department of Education. This report is available on the IES website at http://ies.ed.gov/ncser/.

`mdes.bira3r1, mrss.bira3r1, optimal.bira3r1`

1 2 3 4 5 6 | ```
## Not run:
power.bira3r1(rho3=.20, rho2=.15, omega3=.10, omega2=.10,
n=69, J=10, K=100)
## End(Not run)
``` |

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