Calculate the N required to estimate the ICC with a desired confidence interval
Calculate the N required to estimate the ICC with a desired confidence interval
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(Bonett 2002).
Nest( est.type = c("hypothetical","pilot"), w, ICC =NULL, k =NULL, x =NULL, y =NULL, data =NULL, alpha =0.05)
Arguments
est.type: A character string of either "hypothetical" indicating usage of the given values of k and ICC or if "pilot"
is specified then to calculate these from the dataset provided. Just the first letter may be used.
w: A numeric of desired width for the confidence interval about the ICC estimate.
ICC: The expected intraclass correlation coefficient.
k: The number of measurements per individual or group.
x: A column name of data indicating the individual or group ID from a pilot study.
y: A column name of data indicating the measurements from a pilot study.
data: A data.frame from a pilot experiment.
alpha: The alpha level to use when estimating the confidence interval.
Returns
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.
Details
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.
Examples
# 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))
References
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, 3(1):129-137.