Can Bayesian mediation be conducted in JASP?

DaveB

I thought I saw that Bayesian mediation could be conducted in JASP, but don't see it anywhere (including under SEM < Mediation Analysis? If not, does anyone know of another GUI stats program that allows for Bayesian mediation?

Thanks!

patc3

I don't think you can do it automatically through a menu, but you can do it through the JAGS module. Here's a syntax where x = Extraversion, m = Satisfaction, and y = ITL (intention to leave), i.e. extraversion leads to higher satisfaction which in turn leads to lower intention to leave:

model{
# likelihood
for(i in 1:978) # 978 is number of rows
{
Satisfaction[i]~dnorm(mu_m[i],1/sigma_m^2)
ITL[i]~dnorm(mu_y[i],1/sigma_y^2)
mu_m[i]<-beta0_m+betax_m*Extraversion[i]
mu_y[i]<-beta0_y+betam_y*Satisfaction[i]+betax_y*Extraversion[i]
}

# priors
beta0_m~dnorm(0,1/10^3)
betax_m~dnorm(0,1/10^3)
beta0_y~dnorm(0,1/10^3)
betam_y~dnorm(0,1/10^3)
betax_y~dnorm(0,1/10^3)
sigma_m~dunif(1*10^-3,1*10^3)
sigma_y~dunif(1*10^-3,1*10^3)

# parameters
indirect<-betam_y*betax_m
}

Here's what my window looks like:

This replicates the output from the SEM module (since I have noninformative priors):

EJ

Isn't this one of the models in the Process module?

EJ

patc3

Wow you're right, I hadn't realized Bayesian had been implemented in Process. Here's how I replicated the analysis:

patc3

Equivalently you can also specify this using paths (no need for Hayes model numbers):

DaveB

Thank you, this is great! As this is the 1st time I've used JAGS, I can't seem to figure out how to get the parameters into the "Parameters in model" window. Also, how would I include covariates? And multiple (2) mediators? Thanks again, much appreciated.

DaveB

I had neglected to refresh... I had initially done a series of mediation analyses, examining separate models for each mediator (2 mediators) and outcomes (3 different outcomes) using Process; however, reviewers recommended reducing the number of models by using an SEM-based mediation test (e.g., including 2 mediators simultaneously; two outcomes that are independent in the same model [my third outcome is essentially a composite of these two outcomes and would be examined in a separate model]).

Is an SEM-like mediation model testable using Bayesian stats? And if so, can that be done using JAGS?

Thanks!

patc3

To make parameters appear in the "Parameters in model" you need to click ctrl+enter to apply the model you wrote.

Yes it's possible in both JAGS and Process. Why do you prefer JAGS? Here's the setup using the Process module (1 predictor = Age, 2 mediators = Satisfaction and Work.engagement, 2 outcomes = ITL and Extraversion):

Note that you have to add residual covariances between IVs/mediators/outcomes (left-hand checkboxes at the bottom of the screenshot). JAGS is a bit harder for me to specify right this minute because you have to add covariances between predictors/mediators/outcomes, and I don't remember how to do that by heart

To answer your question about how to add control variables: you simply add direct paths from your controls to all mediators and outcomes in the model, e.g. like this (say I'm controlling for Gender):

Both JAGS and Process would give the same results (within Monte Carlo error), they're both equivalent and they're both SEM (you're estimating multiple equations simultaneously)

DaveB

Thanks again (and I'm fine with Process). In running it (simplest version with 1 mediator and 1 outcome, plus 2 covariates), however, I get the following error:

patc3

Don't add paths from controls to IV, only to mediators and outcomes (here it fails because your IV is categorical). Age and mschool shouldn't predict NEGFAMDI (that's your IV right?)