Given a predicted ICC and `k`

measures per individual/group, this function will calculate the `N`

individuals/groups required to obtain a desired confidence interval `w`

(according to Bonett, 2002).

1 2 |

`est.type` |
character string of either |

`w` |
desired width of the confidence interval about the ICC estimate |

`ICC` |
expected intraclass correlation coefficient |

`k` |
number of measurements per individual or group |

`x` |
column name of |

`y` |
column name of |

`data` |
a |

`alpha` |
the alpha level to use when estimating the confidence interval |

More than one `ICC`

or `k`

may be given. In this case, the return value is a dataframe with rows representing the values of the specified ICCs and the columns yield the different `k`

values.

`data.frame`

indicating the N number of individuals or groups to use to estimate the given ICC with a desired confidence interval width. Rows represent different levels of ICC while columns indicate different levels of `k`

measurements per individual/group.

Matthew Wolak matthewwolak@gmail.com

D.G. Bonett. 2002. Statistics in Medicine, 21(9): 1331-1335.

M.E. Wolak, D.J. Fairbairn, Y.R. Paulsen. 2011. Methods in Ecology and Evolution.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
#Example 1
n1<-Nest("h", w=0.14, ICC=0.1, k=10)
n1
#Example 2
data(ChickWeight)
Nest("p", w=0.14, x=Chick, y=weight, data=ChickWeight)
ex2<-ICCest(Chick, weight, ChickWeight)
ex2$UpperCI-ex2$LowerCI #confidence interval width of pilot study
ex2
#Example 3
Nest("h", w=0.14, ICC=seq(0.05, 0.15, 0.05), k=seq(10,12,1))
``` |

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