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Prediction limits for an estimated correlation

Source: R/statpsych2.R
pi.cor.Rd

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 estimated Pearson correlation that is expected in the planned study. A one-sided lower correlation prediction limit is useful as a correlation planning value for the 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.

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 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

Examples

pi.cor(.1, .761, 50, 100, 1)
#>         LL        UL
#>  0.6034092 0.8573224

# Should return:
#         LL        UL
#  0.6034092 0.8573224
 
pi.cor(.1, .761, 50, 100, 3)
#>         LL
#>  0.6428751

# Should return:
#         LL
#  0.6428751