I wondered if there is a way to calculate a confidence interval for omega (hierarchical) using the psych package in R? I know it can be done with ci.reliability in MBESS but psych is more appropriate for the model I am testing. Thank you.
See rcon
example:
library(psych)
n <- 30
r <- seq(0,.9,.1)
d <- r2d(r)
rc <- matrix(r.con(r,n),ncol=2)
t <- r*sqrt(n-2)/sqrt(1-r^2)
p <- (1-pt(t,n-2))*2
r1 <- t2r(t,(n-2))
r2 <- d2r(d)
chi <- r2chi(r,n)
r3 <- chi2r(chi,n)
r.rc <- data.frame(r=r,z=fisherz(r),lower=rc[,1],upper=rc[,2],t=t,p=p,d=d,
chi2=chi,d2r=r2,t2r=r1,chi2r=r3)
round(r.rc,2)
#> r z lower upper t p d chi2 d2r t2r chi2r
#> 1 0.0 0.00 -0.36 0.36 0.00 1.00 0.00 0.0 0.0 0.0 0.0
#> 2 0.1 0.10 -0.27 0.44 0.53 0.60 0.20 0.3 0.1 0.1 0.1
#> 3 0.2 0.20 -0.17 0.52 1.08 0.29 0.41 1.2 0.2 0.2 0.2
#> 4 0.3 0.31 -0.07 0.60 1.66 0.11 0.63 2.7 0.3 0.3 0.3
#> 5 0.4 0.42 0.05 0.66 2.31 0.03 0.87 4.8 0.4 0.4 0.4
#> 6 0.5 0.55 0.17 0.73 3.06 0.00 1.15 7.5 0.5 0.5 0.5
#> 7 0.6 0.69 0.31 0.79 3.97 0.00 1.50 10.8 0.6 0.6 0.6
#> 8 0.7 0.87 0.45 0.85 5.19 0.00 1.96 14.7 0.7 0.7 0.7
#> 9 0.8 1.10 0.62 0.90 7.06 0.00 2.67 19.2 0.8 0.8 0.8
#> 10 0.9 1.47 0.80 0.95 10.93 0.00 4.13 24.3 0.9 0.9 0.9
Created on 2019-12-15 by the reprex package (v0.3.0)
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