dat.crede2010 | R Documentation |
Results from 68 studies on the relationship between class attendence and class performance and/or grade point average in college students.
dat.crede2010
The data frame contains the following columns:
studyid | numeric | study number |
year | numeric | publication year |
source | character | study source (journal, dissertation, other) |
sampleid | numeric | sample within study number |
criterion | character | criterion variable (grade, gpa) |
class | character | class type (science, nonscience) |
ni | numeric | sample size |
ri | numeric | observed correlation |
The 68 studies included in this dataset provide information about the relationship between class attendance of college students and their performance (i.e., grade) in the class and/or their overall grade point average. Some studies included multiple samples and hence the dataset actually contains 97 correlation coefficients.
The dataset was obtained via personal communication. Note that this dataset differs just slightly from the one used by Credé et al. (2010).
education, correlation coefficients, multilevel models
Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org
Personal communication.
Credé, M., Roch, S. G., & Kieszczynka, U. M. (2010). Class attendance in college: A meta-analytic review of the relationship of class attendance with grades and student characteristics. Review of Educational Research, 80(2), 272–295. https://doi.org/10.3102/0034654310362998
### copy data into 'dat' and examine data dat <- dat.crede2010 head(dat, 18) ## Not run: ### load metafor package library(metafor) ### calculate r-to-z transformed correlations and corresponding sampling variances dat <- escalc(measure="ZCOR", ri=ri, ni=ni, data=dat) ############################################################################ ### meta-analysis for the relationship between attendance and grades res <- rma(yi, vi, data=dat, subset=criterion=="grade") res ### estimated average correlation with 95% CI/PI predict(res, transf=transf.ztor, digits=2) ### examine if relationship between attendance and grades differs for nonscience/science classes res <- rma(yi, vi, mods = ~ class, data=dat, subset=criterion=="grade") res ### estimated average correlations for nonscience and science classes predict(res, newmods=c(0,1), transf=transf.ztor, digits=2) ### examine if relationship between attendance and grades has changed over time res <- rma(yi, vi, mods = ~ year, data=dat, subset=criterion=="grade") res ############################################################################ ### meta-analysis for the relationship between attendance and GPA res <- rma(yi, vi, data=dat, subset=criterion=="gpa") res ### estimated average correlation with 95% CI/PI predict(res, transf=transf.ztor, digits=2) ### examine if relationship between attendance and GPA has changed over time res <- rma(yi, vi, mods = ~ year, data=dat, subset=criterion=="gpa") res ############################################################################ ### use a multilevel model to examine the relationship between attendance and grades res <- rma.mv(yi, vi, random = ~ 1 | studyid/sampleid, data=dat, subset=criterion=="grade") res predict(res, transf=transf.ztor, digits=2) ### use a multilevel model to examine the relationship between attendance and gpa res <- rma.mv(yi, vi, random = ~ 1 | studyid/sampleid, data=dat, subset=criterion=="gpa") res predict(res, transf=transf.ztor, digits=2) ## End(Not run)
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