dat.craft2003 | R Documentation |
Results from 10 studies on the relationship between the Competitive State Anxiety Inventory-2 (CSAI-2) and sport performance.
dat.craft2003
The data frame contains the following columns:
study | numeric | study number |
ni | numeric | sample size |
sport | character | type of sport (T = team sport, I = individual sport) |
ri | numeric | correlation coefficient |
var1 | character | variable 1 of the correlation coefficient (see ‘Details’) |
var2 | character | variable 2 of the correlation coefficient (see ‘Details’) |
The 10 studies included in this dataset are a subset of the studies included in the meta-analysis by Craft et al. (2003) on the relationship between the Competitive State Anxiety Inventory-2 (CSAI-2) and sport performance.
The CSAI-2 has three subscales: cognitive anxiety (acog
), somatic anxiety (asom
), and self-confidence (conf
). The studies included in this dataset administered the CSAI-2 prior to some sport competition and then measured sport performance based on the competition. Most studies provided all 6 correlations (3 for the correlations among the 3 subscales and 3 for the correlations between the subscales and sport performance), but 2 studies (with study numbers 6 and 17) only provided a subset.
psychology, correlation coefficients, multivariate models
Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org
Becker, B. J., & Aloe, A. M. (2019). Model-based meta-analysis and related approaches. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (3nd ed., pp. 339–363). New York: Russell Sage Foundation.
Craft, L. L., Magyar, T. M., Becker, B. J., & Feltz, D. L. (2003). The relationship between the Competitive State Anxiety Inventory-2 and sport performance: A meta-analysis. Journal of Sport and Exercise Psychology, 25(1), 44–65. https://doi.org/10.1123/jsep.25.1.44
### copy data into 'dat' and examine data dat <- dat.craft2003 head(dat, 18) ## Not run: ### load metafor package library(metafor) ### construct dataset and var-cov matrix of the correlations tmp <- rcalc(ri ~ var1 + var2 | study, ni=ni, data=dat) V <- tmp$V dat <- tmp$dat ### examine data for study 1 dat[dat$study == 1,] V[dat$study == 1, dat$study == 1] ### examine data for study 6 dat[dat$study == 6,] V[dat$study == 6, dat$study == 6] ### examine data for study 17 dat[dat$study == 17,] V[dat$study == 17, dat$study == 17] ### multivariate random-effects model res <- rma.mv(yi, V, mods = ~ var1.var2 - 1, random = ~ var1.var2 | study, struct="UN", data=dat) res ## End(Not run)
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