It generates correlation matrices with the parametric bootstrap on the univariate R (uniR) object.
bootuniR1(x, Rep, nonPD.pop=c("replace", "nearPD", "accept"))An object of class 'uniR1'
Number of replications of the parametric bootstrap
If it is replace, generated non-positive
definite matrices are replaced by generated new ones which are
positive definite. If it is nearPD, they are replaced by
nearly positive definite matrices by calling
Matrix::nearPD(). If it is accept, they are accepted.
An object of the generated correlation matrices.
This function implements the parametric bootstrap approach suggested by Yu et al. (2016). It is included in this package for research interests. Please refer to Cheung (2018) for the issues associated with this parametric bootstrap approach.
Cheung, M. W.-L. (2018). Issues in solving the problem of effect size heterogeneity in meta-analytic structural equation modeling: A commentary and simulation study on Yu, Downes, Carter, and O'Boyle (2016). Journal of Applied Psychology, 103, 787-803.
Yu, J. (Joya), Downes, P. E., Carter, K. M., & O'Boyle, E. H. (2016). The problem of effect size heterogeneity in meta-analytic structural equation modeling. Journal of Applied Psychology, 101, 1457-1473.