Confidence interval for an average Cronbach alpha reliability

Source: R/meta_ave.R

Computes the estimate, standard error, and confidence interval for an average Cronbach reliability coefficient from two or more studies.

meta.ave.cronbach(alpha, n, rel, r, bystudy = TRUE)

Arguments

alpha

alpha level for 1-alpha confidence

n

vector of sample sizes

rel

vector of sample reliabilities

r

number of measurements (e.g., items) used to compute each reliability

bystudy

logical to also return each study estimate (TRUE) or not

Value

Returns a matrix. The first row is the average estimate across all studies. If bystudy is TRUE, there is 1 additional row for each study. The matrix has the following columns:

  • Estimate - estimated effect size

  • SE - standard error

  • LL - lower limit of the confidence interval

  • UL - upper limit of the confidence interval

References

Bonett DG (2010). “Varying coefficient meta-analytic methods for alpha reliability.” Psychological Methods, 15(4), 368--385. ISSN 1939-1463, doi:10.1037/a0020142 .

Examples

n <- c(583, 470, 546, 680)
rel <- c(.91, .89, .90, .89)
meta.ave.cronbach(.05, n, rel, 10, bystudy = TRUE)
#>         Estimate          SE        LL        UL
#> Average   0.8975 0.003256081 0.8911102 0.9038592
#> Study 1   0.9100 0.005566064 0.8985763 0.9204108
#> Study 2   0.8900 0.007579900 0.8743616 0.9041013
#> Study 3   0.9000 0.006391375 0.8868623 0.9119356
#> Study 4   0.8900 0.006297549 0.8771189 0.9018203

# Should return:
#         Estimate          SE        LL        UL
# Average   0.8975 0.003256081 0.8911102 0.9038592
# Study 1   0.9100 0.005566064 0.8985763 0.9204108
# Study 2   0.8900 0.007579900 0.8743616 0.9041013
# Study 3   0.9000 0.006391375 0.8868623 0.9119356
# Study 4   0.8900 0.006297549 0.8771189 0.9018203