Testing Mediated Moderation Models: Steps 1-2

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From the course by University of Virginia

Understanding Your Data: Analytical Tools

22 оценки

University of Virginia

Understanding Your Data: Analytical Tools

22 оценки

Are you trying to understand data from your research? Learn how and when to conduct mediation, moderation, and conditional indirect effects analyses? Or, perhaps, how to theorize and test your theoretical models? If so, this is the course for you! We will walk you through the steps of conducting multilevel analyses using a real dataset and provide articles and templates designed to facilitate your learning. You'll leave with the tools you need to analyze and interpret the results of the datasets you collect as a researcher. By the end of this course, you will understand the differences between mediation and moderation and between moderated mediation and mediated moderation models (conditional indirect effects), and the importance of multilevel analysis. Most important, you will be able to run mediation, moderation, conditional indirect effect and multilevel models and interpret the results. This course is supported by the BRAD Lab at the Darden School of Business, which studies organizational behavior, marketing, business ethics, judgment and decision-making, behavioral operations, and entrepreneurship, among other areas. More: http://www.darden.virginia.edu/brad-lab/

From the lesson

Conditional Indirect Effects

Now that you know more about mediation and moderation, let's take a look at conditional indirect effects models, which are a combination of mediation and moderation models. First we will get to the heart of the differences between moderated mediation and mediated moderation models.This will allow you to fully understand the relationships between independent variables and dependent variables. By the end of the module, you will be able to theorize about conditional indirect effect models on SPSS and to test which path of the mediation model is affected by the moderator. Then you'll dive into SPSS, run different models, and learn how to interpret the results.

Conditional Indirect Effects: Mediated Moderation Models8:17

Testing Mediated Moderation Models: Steps 1-25:48

Testing Mediated Moderation Models: Steps 3-56:50

Moderated Mediation Models Overview7:30

Testing First Stage Moderated Mediation Models8:55

Second Stage Moderated Mediation Models Overview5:11

Testing Second Stage Moderated Mediation Models9:57

Dual Stage Moderated Mediation Models Overview5:18

Testing Dual Stage Moderated Mediation Models11:27

Meet the Instructors

Cristiano Guarana
Post-Doctoral Researcher
Darden School of Business

Welcome to our second session

of our second workshop on conditional interactive facts.

This time we'll be talking about mediated moderation and

we'll show you how to conduct an analysis on mediated moderation models.

In the prior session, we went through the theory behind mediated moderation models.

Now we'll get our data and run some analysis.

So this is the agenda for today.

We'll be testing for mediated moderation models.

And we'll go through all these steps as we progress.

So the first step is actually conducting a traditional test of moderation on the DV.

The second step is conducting a traditional moderation test

on the mediator.

So the only difference is that we are changing our dependent variable

instead of using our distal dependent variable,

we are using the mediator as our dependent variable in our Step 2.

And then in Step 3, we will conduct and analysis using process and

specifically the model 8 on the PROCESS macro developed by Hayes.

If you don't have that PROCESS macro installed on your computer,

this is a good time to install it.

So you can download this PROCESS macro and then install on your computer.

We need that macro to run this analysis.

And then, we'll conduct a bootstrapping analysis, that's our Step 4.

And in Step 5, we'll look at the index of moderated mediation.

That index is something new that Hayes created for us, so there is a paper and

you can download this paper by clicking on the link in the description of this video.

So feel free to go there and download that

paper if you wanted to know more about the index of moderated mediation.

So let's do it.

Let's run an analysis.

And this is the model we'll be testing today.

We'll keep it constant with our first workshop,

so we'll be using job meaningfulness in the job performance.

And what we are theorizing here is that

meaningfulness influences job performance, and that relationship is

a function of the organization identification of the employee.

And then we theorize that this interaction term is explained,

the effects of this interaction term is explained by job engagement.

Let's do it.

So the first step is testing for an interaction term and

the effects of that interaction on job performance.

Again, this is a very similar, it's a simple test and

you've done this in one of our prior sessions in which we

walked through the moderation models.

So if you are not familiar, if you need more information on moderations,

go to that particular session in our Workshop 1.

So here we'll go to Analyze > Regression and

again click on the PROCESS macro by Hayes.

Enter the information on this screen.

And we have as our dependent variable, performance.

As independent variable, meaningfulness.

As our moderator, organization identification.

Here we needed to select the correct model, which is model number 1.

Go to Options and select the Mean center for

products, that's important to avoid multicollinearity issues.

And also print the covariance matrix.

Then click on OK.

So this is information that you get from that analysis.

And remember, we'll be looking at the relationship of the interaction term and

our dependent variable performance in this case.

We find that the interaction term is significant.

And then you'll scroll down the output file and

you'll see that for high levels of organization identification,

the direct effect of job meaningfulness on job performance is significant.

But for low levels of organization identification?

No, there is 0 in the confidence interval.

And then, we are ready for a Step 2.

And for a Step 2, we conduct the same moderation test,

but now instead of using job performance as an outcome,

we use job engagement, our mediator.

You run the same test, go to PROCESS, enter all the variables.

But again, instead of using job performance our dependent variable,

as our outcome, we use our mediator, job engagement.

Don't forget to select model number one to conduct moderation analysis.

The same set of outputs that you want.

Important, again, to select Mean center for

products and to print the covariance matrix.

Click on OK.

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