pi.cor: Prediction limits for a sample correlation in a future study

In statpsych: Statistical Methods for Psychologists

Prediction limits for a sample correlation in a future study

Description

Computes approximate one-sided or two-sided prediction limits for the estimated Pearson correlation in a future study with a planned sample size of n. The prediction interval uses a correlation estimate from a prior study that had a sample size of n0.

Several confidence interval sample size functions in this package require a planning value of the expected sample value of a Pearson correlation in the planned study. A one-sided lower correlation prediction limit is useful as a correlation planning value for a conservatively large sample size required to obtain a confidence interval with desired width. This strategy for specifying a correlation planning value is useful in applications where the population correlation in the prior study is assumed to be very similar to the population correlation in the planned study.

For more details, see Section 1.26 of Bonett (2021, Volume 2)

Usage

pi.cor(alpha, cor, n0, n, type)

Arguments

alpha	alpha value for 1-alpha confidence
cor	estimated Pearson correlation from prior study
n0	sample size used to estimate the correlation in prior study
n	planned sample size of future study
type	set to 1 for two-sided prediction interval set to 2 for one-sided upper prediction limit set to 3 for one-sided lower prediction limit

Value

Returns one-sided or two-sided prediction limit(s) of an estimated Pearson correlation in a future study

References

\insertRef

Bonett2021statpsych

Examples

pi.cor(.1, .761, 50, 100, 1)

# Should return:
#      LL     UL
#  0.6034 0.8573
 
pi.cor(.1, .761, 50, 100, 3)

# Should return:
#      LL
#  0.6429
 

statpsych documentation built on Jan. 13, 2026, 1:07 a.m.