pi.r: Correlation prediction interval

In predictionInterval: Prediction Interval Functions for Assessing Replication Study Results

Description

Correlation prediction interval

Usage

pi.r(r, n, rep.n = NA, prob.level = 0.95)

Arguments

r	Original study: Correlation
n	Original study: Sample size
rep.n	(optional) Replication study: Sample size. If not specified, n is used.
prob.level	(optional 0 to 1 value) Probability level desired (0 to 1). If not specified .95 (i.e., 95 percent) will be used.

Value

The prediction interval and related statistics in list format.

Examples

pi.r(r=.35,n=100,rep.n=200)

Example output

Original study: r = 0.35, N = 100, 95% CI[0.16, 0.51]
Replication study: N = 200
Prediction interval: 95% PI[0.13,0.56].


Interpretation:
The original correlation is 0.35 - with a prediction interval 95% PI[0.13, 0.56] based a replication sample size of N = 200. If the replication correlation differs from the original correlation only due to sampling error, there is a 95% chance the replication result will fall in this interval. If the replication correlation falls outside of this range, factors beyond sampling error are likely also responsible for the difference.

predictionInterval documentation built on May 1, 2019, 10:13 p.m.