ci.rsqr: Confidence interval for squared multiple correlation

In statpsych: Statistical Methods for Psychologists

Confidence interval for squared multiple correlation

Description

Computes an approximate confidence interval for a population squared multiple correlation in a linear model with random predictor variables. This function uses the scaled central F approximation method. An approximate standard error is recovered from the confidence interval.

For more details, see Section 2.4 of Bonett (2021, Volume 2)

Usage

ci.rsqr(alpha, r2, s, n)

Arguments

alpha	alpha value for 1-alpha confidence
r2	estimated unadjusted squared multiple correlation
s	number of predictor variables
n	sample size

Value

Returns a 1-row matrix. The columns are:

• R-squared - estimate of unadjusted R-squared (from input)

• adj R-squared - bias adjusted R-squared estimate

• SE - recovered standard error

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

References

\insertRef

Helland1987statpsych

\insertRef

Bonett2021statpsych

Examples

ci.rsqr(.05, .247, 4, 150)

# Should return:
# R-squared adj R-squared      SE      LL     UL  
#     0.247        0.2262 0.06024  0.1152 0.3514
 

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