ci.rsqr {statpsych} | R Documentation |
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.
ci.rsqr(alpha, r2, s, n)
alpha |
alpha value for 1-alpha confidence |
r2 |
estimated unadjusted squared multiple correlation |
s |
number of predictor variables |
n |
sample size |
Returns a 1-row matrix. The columns are:
R-squared - estimate of unadjusted R-squared
adj R-squared - bias adjusted R-squared estimate
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
Helland IS (1987). “On the interpretation and use of R2 in regression analysis.” Biometrics, 43(1), 61-69. doi: 10.2307/2531949.
ci.rsqr(.05, .241, 3, 116) # Should return: # R-squared adj R-squared LL UL # [1,] 0.241 0.2206696 0.09819599 0.3628798