Studies on the Reliability of the CES-D Scale
Results from 9 studies on the reliability of the Center for Epidemiologic Studies Depression (CES-D) Scale administered to children providing care to an elderly parent.
dat.bonett2010
The data frame contains the following columns:
| study | numeric |
study number |
| source | character |
source of data |
| ni | numeric |
sample size |
| mi | numeric |
number of items in the scale |
| ai | numeric |
observed value of Cronbach's alpha |
| caregivers | character |
gender of the children in the sample |
The Center for Epidemiologic Studies Depression (CES-D) Scale is a 20-item questionnaire assessing various symptoms of depression, with each item scored on a 4-point scale. The scale has been used in several studies to examine depressive symptoms in children providing care to an elderly parent. The dataset includes information on the reliability of the scale as measured with Cronbach's alpha in 9 such studies. Also, the gender composition of the children in each sample is indicated.
Bonett, D. G. (2010). Varying coefficient meta-analytic methods for alpha reliability. Psychological Methods, 15, 368–385.
Bonett, D. G. (2002). Sample size requirements for testing and estimating coefficient alpha. Journal of Educational and Behavioral Statistics, 27, 335–340.
Hakstian, A. R., & Whalen, T. E. (1976). A k-sample significance test for independent alpha coefficients. Psychometrika, 41, 219–231.
### copy data into 'dat' and examine data dat <- dat.bonett2010 dat ### meta-analysis using the raw alpha values res <- rma(measure="ARAW", ai=ai, mi=mi, ni=ni, data=dat) res ### meta-analysis using transformed alpha values (using the ### transformation suggested by Hakstian & Whalen, 1976) res <- rma(measure="AHW", ai=ai, mi=mi, ni=ni, data=dat) res predict(res, transf=transf.iahw) ### meta-analysis using transformed alpha values (using the ### transformation suggested by Bonett, 2002) res <- rma(measure="ABT", ai=ai, mi=mi, ni=ni, data=dat) res predict(res, transf=transf.iabt) ### examine whether female/mixed samples yield different alphas (with raw alphas) res <- rma(measure="ARAW", ai=ai, mi=mi, ni=ni, mods = ~ caregivers, data=dat) res predict(res, newmods=c(0,1), digits=2)
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