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The PROCESS module

License: GNU General Public License v3.0

QML 1.86% R 98.14%
jasp mediation-analysis moderation-analysis regression statistics

jaspprocess's Introduction

The PROCESS Module

RSD

A JASP implementation of the PROCESS macro for SPSS developed by Andrew Hayes. Test and compare causal and conditional process models using mediation, moderation, and moderated mediation analyses.

Reference

Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis (3rd Ed.). New York: The Guilford Press.

Hayes, A. F. (2022). The PROCESS macro for SPSS, SAS, and R (Version 4.2) [Computer software]. https://processmacro.org

jaspprocess's People

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jaspprocess's Issues

Interaction between X and M in Mediation Models

The indirect and direct effects in models that PROCESS estimates are calculated assuming no interaction between the variable specified as X and any mediator. This assumption can be tested, i.e. the null hypothesis of no interaction between the mediator and X. This would be in lign with further testing the appropriateness of the model like the local tests do

Add more footnotes

We should add more footnotes about the assumptions and implications of process models.

Error when residual covariances, independent variables is NOT selected when having multple IVs

Witihn Bayesian Proces module, when I create a mediation model and an additional direct effect of an extra IV on the DV, I get the following error (see below). This occurs when residual covariances, independent variables is NOT selected

Error in if (varx = 0) {: missing value where TRUE/FALSE needed

Stack trace
(function (mod, ll)
{
rEff <- .procBayesCalcRelEff(mod, ll)
return(loo::loo(ll, r_eff = rEff))
})(mod = dots[[1]][[1]], ll = dots[[2]][[1]])

.procBayesCalcRelEff(mod, ll)

loo::relative_eff(exp(logLik), chain_id = chainId)

relative_eff.matrix(exp(logLik), chain_id = chainId)

relative_eff.array(x, cores = cores)

apply(x, 3, ess_rfun)

FUN(array(newX[, i], d.call, dn.call), ...)

lapply(1:chains, FUN = function(i) posterior::autocovariance(sims[, i]))

FUN(X[[i]], ...)

posterior::autocovariance(sims[, i])

To receive assistance with this problem, please report the message above at: https://jasp-stats.org/bug-reports

image

Factors in three-way interactions cause error

When a factor is involved in a moderated moderation, it causes an error because the factor variable cannot be multiplied with other variables when computing ind_mod1_mod2 in the dataset.

Fix graph layouts

For multiple mediators, and moderated moderation the path plots still look a bit cluttered.

Plotting multiple moderations (e.g. model 8) and moderated moderations (e.g. model 12)

In case of a moderater moderating multiple paths simultanuously (such as model 8), the conceptual path plot misses an edge. Building on this, in case of moderated moderation involving multiple paths (such as in model 12), likewise the conceptual path plot misses the moderation edge and moderated moderation edge. The statistical path plots are correct, though.

Bayesian Process issues

Just tried the Bayesian process analysis, but quickly ran into some issues:

  • there is no runjags package
    image

  • dim(x) positive length when Hayes model not fully configured?

see attached jasp file (change ext)
bayesprocerrors.zip

Fix bootstrapping

Bootstrapping is not properly working currently. Also, we should add a footnote to tables when CIs are bootstrapped.

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