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.

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

• 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

Examples

ci.rsqr(.05, .241, 3, 116)

# Should return:
#      R-squared adj R-squared         SE         LL        UL  
# [1,]     0.241     0.2206696 0.06752263 0.09819599 0.3628798
 

statpsych documentation built on July 9, 2023, 6:50 p.m.