prec_icc: Sample size or precision for an intraclass correlation

In presize: Precision Based Sample Size Calculation

Sample size or precision for an intraclass correlation

Description

prec_icc returns the sample size or the precision for the given intraclass correlation.

Usage

prec_icc(rho, k, n = NULL, conf.width = NULL, conf.level = 0.95)

Arguments

rho	desired intraclass correlation.
k	number of observations per n (subject).
n	number of subjects.
conf.width	precision (the full width of the confidence interval).
conf.level	confidence level.

Details

Exactly one of the parameters n or conf.width must be passed as NULL, and that parameter is determined from the others.

Sample size or precision is calculated according to formula 3 in Bonett (2002), which is an approximation. Whether ICC is calculated for a one-way or a two-way ANOVA does not matter in the approximation. As suggested by the author, 5*rho is added to n, if k = 2 and rho ≥ 7. This makes the assumption that there is no interaction between rater and subject.

n is rounded up to the next whole number using ceiling.

Value

Object of class "presize", a list of arguments (including the computed one) augmented with method and note elements.

References

Bonett DG (2002). Sample size requirements for estimating intraclass correlations with desired precision. Statistics in Medicine, 21:1331-1335. doi: 10.1002/sim.1108

Examples

# Bonett (2002) gives an example using 4 raters, with an ICC of 0.85 and want
# a confidence width of 0.2. Bonett calculated that a sample size of 19.2 was
# required. This can be done via
prec_icc(0.85, 4, conf.width = 0.2)
# note that \code{presamp} rounds up to the nearist integer.

# Bonett then goes on to estimate the width given the sample size, finding a
# value 'close to 0.2':
prec_icc(0.85, 4, 20)

presize documentation built on March 7, 2023, 8:28 p.m.