tssemParaVar: Estimate the heterogeneity (SD) of the parameter estimates of the TSSEM object

Description

It estimates the heterogeneity of the parameter estimates of the TSSEM objects using either the bootstrap or the delta methods.

Usage

tssemParaVar(tssem1.obj, tssem2.obj, method=c("bootstrap", "delta"),
             interval=0.8, Rep=50, output=c("data.frame", "matrices"),
             nonPD.pop=c("replace", "nearPD", "accept"))

Arguments

tssem1.obj

An object of class tssem1REM returned from tssem1()

tssem2.obj

An object of class wls returned from tssem2() or wls()

method

If it is bootstrap, random correlation matrices are sampled from the tssem1.obj by the parametric bootstrap. If it is delta, the delta method is used to estimate the heterogeneity of the parameter estimates.

interval

The desired interval, e.g., .8 or .95.

Rep

The number of parametric bootstrap. It is ignored when the method is delta.

output

Either a data.frame or matrices of the output.

nonPD.pop

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.

Value

Either a data.frame or matrices of the output.

Details

The bootstrap method is based on the discussion in Cheung (2018) and Yu et al. (2016). The delta method is an alternative method to obtain the heterogeneity.

References

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.