Moderated mediation in SPSS using Hayes Process macro (August, 2019)

[@supreetsaluja4787]

thank you so much for your videos. You explain statistical analyses really thoroughly!

[@mikecrowson2462]

Thanks Supreet! Best wishes!

[@liechdinah6560]

Thank you for this video . I have learned so much about Hayes Models

[@prayitno419]

Thank you Mr. Crowson for his knowledge, may you always be healthy and under God's protection🤲🙏

[@stevenkatoriorfa8091]

This was greatly taught. Thanks so much. I learned a lot.

[@mikecrowson2462]

I appreciate it, Steven! Cheers!

[@intuition6675]

Thank you so much for such an enlightening video, Sir!! Thank you so much for sharing knowledge 🙏❤!!!

[@jianaiyeow5761]

thank you prof for all the explanation. it is so helpful and clear a lot of doubts. i started to know how to interpret the data output and thanks for sharing the 'copy of data' as demo. truly appreciate your kind help

[@ElimelchRT]

you are doing a great service to us! thank you!

[@jackcincotta1135]

Great video; easy to comprehend!

[@mikecrowson2462]

Thanks Jack! Best wishes!

[@milliondollarman123]

Excellent demonstration!

[@lilywisker6018]

Thanks so much - A very helpful tutorial.

[@mikecrowson2462]

Hi Lily, thank you for visiting! I also wanted to let you know that I have some newer videos out on moderated mediation from this spring. You might check out: kzbin.info/www/bejne/pYqwh2uvjNCSbbs kzbin.info/www/bejne/Z5fMf6h9qb2WbKs kzbin.info/www/bejne/pHTLYmWJfb2DpZI kzbin.info/www/bejne/kF6Wma2BZ8t2bMk Best wishes!

[@kristinastuhler5941]

Thank God you posted the slides too...SO HELPFUL

[@mikecrowson2462]

I'm glad they were helpful! Thanks for visiting my site!

[@mariamaravilla1977]

You're a great teacher.

[@georgeochieng8954]

Thank you, this helped plenty especially the caveat of two IV's

[@benyazici]

Great and Helpful video, thanks alot

[@sadafpouriliyaei9068]

Thank you. Very helpful!

[@yulinliu850]

Excellent! Thank you!

[@mikecrowson2462]

I appreciate you visiting, Yulin!

[@jaynastics2]

Very helpful video!

[@amelmechti1523]

Thank you very much!

[@nono-yd1tw]

Thank you for this video. Can you run a PROCESS model 14 moderated mediation with a dichotomous moderator variable?

[@The13thTrip]

Thank you very much! I appreciate the clarity of your explanations, both in terms of conducting the analyses and what the results indicate/suggest. PROCESS isn't the easiest thing to understand...even among us with Ph.Ds. I suspect your videos are indirectly advancing research. Cheers, Mike!

[@mikecrowson2462]

That's very kind to say. I appreciate you visiting and taking the time to comment. Best wishes to you!

[@jalan2dibelanda]

I have watched a number of your videos in the last one week! I've found them of high quality! I hope that you could make a video explaining Model 14 just like the way you explained Model 7 here. And perhaps with multiple controlled variables (e.g., 1 dichotomous variable + 1 continuous variable). :)

[@hinamunirbutt1895]

thank you. appreciated.

[@cailawrance8369]

Thank you so much for sharing, Prof Crowson! Meanwhile, do you know how to perform the sensitivity analysis and find the effect size for moderated mediation model? Thank you very much!!

[@ceydakoc8016]

very good video thanks for this tutorial :)

[@yingzhu552]

THANKS A MILLION!!!!!

[@sevincapti6125]

Thank you very much for this great video! What needs to be done in case of more than one independent variable?

[@mikecrowson2462]

If you have more than one independent variable with paths not assumed to be moderated by a variable W, then you can simply add them in as covariates and direct effects of these variables on the DV can be estimated directly. Best wishes!

[@TankAqil]

Mike Crowson How can we do moderated mediation with more than 1 IV? Thanks :)

[@ArifPartono]

Dear Mr Crowson .. Thank you for the video, it helps me a lot. I still need one more favour if you have. it is regarding with the presentation in the journal article. Do you have an example how we should present these figures in a paper? thank you.

[@anhnguyenvan5857]

Thank you very much for your great videos. If my model has to use second-order constructs (multi-dimensions) how can I do. Should I have to calculate the means of the construct based on factor loading items, please?

[@sabrafarrukh9857]

Thank you Mike for wonderful video on moderation and mediation effects. Kindly upload or send me PPT and video for model 5. How to theorizing, testing and write up of model 5, which is Direct Effect of Moderation.

[@agustinvidalbuitano9529]

Hello, do you have that PPT? I am currently developing a model and I used the model 5, but i did not find so much information about how to interpret and write the hypothesis.. I will really apreciate if you have something that can help me. Thanks in advance.

[@denniarli]

Thank you Mike, appreciate the video!

[@ItratBatool-hf9xy]

@Mike Crowson this video is very helpful moderator and independent variables in my research model are both categorical with two levels each. dependent variable is continuous i have applied research model 8 and but i don't know how to interpret directional conditional effects... should i look at conditional effects to assess the results of the moderation?

[@jackycheah8075]

Hi Mike, thanks a bunch for this tutorial. I just wonder do you have ways to generate a moderated mediation plot (maybe Model 7) based on the conditional indirect effect result.

[@dr.olabawazir]

Thank you for your helpful videos .. How can I get the results of moderation model with the percentile levels...I appreciate your cooperation

[@mikecrowson2462]

Hi there. The confidence intervals are given for the regression coefficients as LLCI and ULCI for upper and lower bound of the confidence interval. The percentile bootstrap applied when bootstrapping is provided as: BootLLCI and BootULCI. The default is 95% confidence intervals. You can change that default on the main menu screen by using the Confidence Intervals drop down. And if you want bootstrap confidence intervals for your regression parameters, just click the little box for bootstrap inference for model coefficients. I hope this helps!

[@dr.olabawazir]

@@mikecrowson2462 thank you so much 😊

[@drnkululekofuyane3730]

Mike, thanks a lot for the video, so helpful it was. The question is, how would you interpret when your output indicates that the IV isn't significant but the MV is. For example, when the IV (rumcen) is insignificant and the moderator (concern) is significant.

[@wilberforcejahonga194]

This is impressive. I am however lost in differentiating between moderator and mediator variable.

[@mikecrowson2462]

Hello. A moderator variable is one that alters or changes the relationship between two other variables. In other words, the relationship between X and Y is conditional depending on the level of variable Z. You can think of a moderator as answering the 'when' question as it pertains to the relationship between X and Y. For example, when the moderator z equals some value, the relationship between X and Y takes on one value. When then moderator z equals some other value, then the relationship between X and Y is something else. A mediator variable is one that theoretically 'transmits' the variation from X to Y. For instance, we might say that the effect of mastery goals (X) on student achievement (Y) is accounted for by deeper cognitive engagement (M). So the proposed causal path would be: mastery goals (X)-->engagement (M)-->achievement. The classic article on the distinction between mediators and moderators is Baron & Kenny (1986). You should be able to download a copy from the web at this address (I quickly googled to locate a copy): www.sesp.org/files/The%20Moderator-Baron.pdf

[@Wangster127]

If the indirect effects are significant on all levels of the moderator, but the index of moderated mediation is not significant, could we interpret the result as there is mediation in this model and on all levels of W, the effect of X and W on Y is mediated by the mediating variable? I hope that question makes sense! I just wanted to make sure that even though the index of moderated mediation is nonsignificant, it does not mean there isn't mediation because if the indirect effects are significant for both levels of the moderator, this can be interpreted as that mediator mediates X on Y on all levels of W.

[@aaminahzamanmalik8320]

Is there any way of doing process model 14 in amos?

[@wilberforcejahonga194]

Thanks again. My second question is whether the Hayes process macro is applicable to ordinal/nominal data.

[@mikecrowson2462]

Process does allow you to include nominal and ordinal variables in various ways. However, how they can be included depends on the model you are running. If you are performing a mediation analysis, then the IV (X) can be nominal or ordinal (if doing this, you would indicate to the program that the variable is categorical using the 'Categorical option). The only categorical outcome (Y) you can use in a mediation model is a binary outcome variable. If you have a binary outcome, Process will recognize it and will run a logistic regression as the second regression in your path model. If you are running a moderated multiple regression then your IV and/or Moderator variable can be categorical. The DV can also by binary (as described above). If it is binary then then regression will be a moderated binary logistic regression. There are other more complicated models that incorporate mediation and moderation and with various 'rules' for what types of variables can be included. In general, the above rules for mediators, moderators, and outcome variables stand. There is NO mechanism to explicitly specify a mediator as categorical. If your mediator is nominal (for instance), the program will run OLS regression for that portion of your mediator model, which will give you incorrect results. If your mediator is ordinal, it will do the same thing (although this might be a more justifiable approach to testing mediation if you have enough scale points; but there is debate on this issue; but there is debate on this point). Hope this helps. Cheers!

[@MsLavyB]

Hi Dr. Crowson! Is Model 14 interpreted the same way as Model 7, but at different points? Could you do a video on model 14? LaVonya

[@jalan2dibelanda]

I have just written a similar comment. :D

[@soehartosoeharto8471]

is there any reason for centering variables? can we use the raw data for variable?

[@mikecrowson2462]

There's actually a couple of centering options in Process. Usually, I will mean center the continuous predictor variables to facilitate interpretation. However, technically mean centering is not a requirement. Since moderated mediation involves at least one regression in comprising the full model including an interaction term (capturing the moderated effect), it might be worth reviewing that topic. Here is a video you might check out: kzbin.info/www/bejne/gIuVl59umt2Biqc

[@soehartosoeharto8471]

@@mikecrowson2462 thank you Prof for valuable answers

[@piun6705]

thanks for this video, Mike. I'm not sure why am I not able to view Process, is it because its the trial SPSS i am working on, & if yes, how do I then check on the conditional effects of my moderators [& I have two of them on different paths, like Chris below] Thanks.

[@kossonouprunelle7576]

My moderating and mediating variable are all ordinal categorical variable, can i use this method to analyse them?

[@Slixcr7junior]

Hello Mike, Thank you for your interesting videos. I have a question about the model 18 : I have 5 X , 6 M and 5 Y. I tested conditionnal indirect effects of X in Y at the values of the 2 moderators. The problem is that in many analysis, I have some significatives indirects effects at the value of moderators but the index of moderated moderated mediation is not significatif. I don't understand why the index is not significant and how can i interpret the significatives indirects effects of X in Y at the value of moderators With an index not significant ? Thank you for your help.

[@lisa-mariemoulart2692]

I have a question for my masterthesis. So i need to use an moderated mediation model 14 Process Hayes in SPSS. X = colour (green, Blue, yellow) Y = attitude M = sustainability perception W = Age (generation X, Y, Z) So X and W are multicategorical. But it is really not clear for me how to understand these results. Do you have a tutorial video on this? Or could help me understand the results. Thank you in advance. You would really save me and my thesis.

[@OGMadMax]

Thank you so much man! For some reason, I have a moderating variable that has two levels: 0 or 0.7. Therefore, the output is only based on at12:00 is only based on two levels as well. Is this right?

[@mikecrowson2462]

I believe the moderator at that point in the demonstration was originally continuous. At the 12:00 minute mark, I was demonstrating the plotting of simple slopes at 3 (arbitrary) levels of the moderator (i.e., at -1sd, mean, and +1sd). If you have a binary moderator, then I would encourage you not to mean center it, but to leave it in it's original metric and then you'd be plotting only 2 simple slopes (one for each level of your moderator). Best wishes!

[@OGMadMax]

@@mikecrowson2462 Sir thank you for your well educated answer! Have a great day

[@Max-fu7ox]

​@@mikecrowson2462 Would you mean center when both IV and Moderating variables are dummy variables, mediating variable is continuous and DV is dummy?

[@zhijingwang7338]

Hi Mike! Nice video! I have a question: why the model number is 7 here?

[@mikecrowson2462]

Hayes has just simply provided numbers for the different models that are available in Process. As far as I can tell, there is nothing special about his numbering. Best wishes!

[@kritikrishna3652]

Hello Sir. Thank you for the information shared. However, in the first part of the output, if IV-->M is significant, the interaction is significant, but Moderator --> Mediator is not significant, then how to interpret this interaction? Also index of moderated mediation is also significant, Pls help. Thanks

[@touseefkhalid1834]

Thank you sir I was trying to understand since a week but your video did it in 5 minutes. But how can I read graph can u plz help

[@sabnambasu5655]

Thank you for the wonderful video. Sir, I have a question to ask. I am having an insignificant index of moderated mediation but at the same time, I am also having significant conditional direct as well as an indirect effect at all the three levels of the moderator. How do I interpret the result?

[@madhumaurya3968]

Categorically variable can moderate in this model?

[@mikecrowson2462]

Hi Madhu, the answer to your question is 'yes'. You can include categorical moderators. I don't really cover that in this video, except where you have a binary moderator. But technically you can include a categorical moderator with more than two levels. But you'll have to use the Multicategorical option in Process. I don't have a video on using it in the context of moderated mediation models. However, I do have a video on using the multicategorical option in the context of moderated regression. This video (kzbin.info/www/bejne/f3iQd6Geq7mompY) might provide you wish some insight for how to use the option with moderated mediation models. At some point I hope to do something with a multicategorical moderator in moderated mediation. Cheers!

[@madhumaurya3968]

@@mikecrowson2462 sir, actually .. I want to check 3 type of categorical variables as moderator in the model..Is it possible.. to check this and how? Please guide me.

[@corinacrn7684]

Dear Dr. Mike Crowson I am using a process macro for my research. In this study, I would like to calculate moderated mediation. It gives the result of "index of moderated mediation" for Figures 7 and 14. But for the model 58 (this is my model), it only gives the result (now, mean, high). Now, according to these results, could I say that my model has moderated mediation? I think the result is significant since the confidence interval values for low, medium and high do not include zero. I can't be sure as I'm undecided so I would like to ask you. Could you please give some information about the subject, please? I am looking forward to hearing from you. Thanks in advance. Best regards,

[@simonaschamper4743]

Hi Mike, thank you for the great tutorial! It really is very helpful. I was wondering, which model would be appropriate for a moderated mediation (on the a-path) with two moderators? It seems like model 7 only allows for one moderator variable. Would model 9 be the correct one?

[@asthapandey3368]

Hello sir, I have a question which model template should I use in PROCESS when there are two different moderators on the same path in a serial mediation model. Please kindly help

[@bubbyzblue2576]

Dear professor, thank you very much for the lessons. I would like to ask is it possible to conduct moderated mediation with multiple independent variables and categorical moderator (gender) using PROCESS Macro? I'd be thankful if you have a good source of this case. Thank you again and wish you well😊🙏

[@bubbyzblue2576]

I have seen that Hayes models are using one independent variable. I'm curious if I can analyze my model using PROCESS Macro or better using AMOS.

[@mikecrowson2462]

Hi there. I'm pretty sure that you can only test moderation of the mediated effect of only one independent variable at a time. Maybe one day Hayes comes up with a system for testing moderation of multiple paths in a single model. Until then, you probably are better off trying to model using another software. You might look at a software like jamovi (www.jamovi.org/download.html). They have a module in there that would allow you test multiple moderated paths. The only downside is that they don't have tests of an index of moderated mediation like Hayes does. Cheers!

[@riya1441]

Thank you so much!I have a question that in model 58 or 59, the conditional indirect effect that is displayed in the output reflects the moderator's(at different levels) effect between IV and mediator or between mediator and DV ?

[@mikecrowson2462]

The conditional indirect effects represent the indirect effect of the IV on the DV at different levels of the moderator variable. Cheers!

[@Snigdha391]

What do you do for multiple IVs and DVs? run them separately? They are not covariates and gender is hypothesised to moderate the mediational effect of an emotion regulation strategy.

[@linsyk1]

Hi, In my output interaction and index of moderation not significant . But conditional indirect effects are significant. Then how do we interpret the result..

[@mikecrowson2462]

The index of moderated mediation is a test of whether the conditional indirect effects vary across levels of the moderator. It is not a test of the conditional indirect effects themselves (in terms of them being different or not different from zero). So, if the index of moderated mediation is not significant, then you have no evidence of moderated mediation. The fact that the conditional indirect effects are significant is unrelated to whether you have moderated mediation. So given the fact that you have no evidence of moderated mediation, you might re-specify your model as one with only the mediation (without the moderation of the indirect effect). Of course if your original hypothesis was moderation of the mediation, then you should be sure to discuss your original model (moderated mediation) and why you chose to re-specify it as mediation only. By the way, I do have several newer videos on moderated mediation. You might check out: kzbin.info/www/bejne/pYqwh2uvjNCSbbs and kzbin.info/www/bejne/Z5fMf6h9qb2WbKs . Cheers!

[@nickfrye5289]

I’m working with data through a private VPN with no internet access. Is there a way to run moderated mediation models in SPSS without process l?

[@Mina28000]

Hello sir, what justification should be given related to using PROCESS Macro for mediation analysis instead of PLS-SEM? Exactly, how is PROCESS better than PLS-SEM?

[@misbahfaiz9398]

Hi , I was using model 21 and process macro giving zero value for effect, bootse, bootllci, bootulci for indirect effect. Any idea why so? This is when I am adding a categorical variable as the moderator.

[@muhammedsabrisirin5324]

Dear Mike İ have analyzed my data with model 59. İn the result all moderator effects is not significant, but İndex of moderated mediation is significant. Is it possible? To analyze the moderated mediation does the moderator effects have to be significant?

[@mikecrowson2462]

Hi Muhammed, the IMM indexes the change in conditional slopes / effects) across levels of your moderator. The simple slopes tests are tests of conditional effects at specific points (eg 16th, 50th, 84th percentiles) of the moderator. These tests are not a test of change in conditional effects, as indexed by IMM. To get a better picture of how slopes vary across the moderator you might request the Johnson Neyman output. These are still simple slopes, but you get a larger number of slopes conditional on the moderator and you can better see the change in slopes over the moderator.

[@muhammedsabrisirin5324]

Dear Mike i will do that analysis. İs there any book or article which explain all principles of moderated mediation analysis? Could you recommend?

[@mikecrowson2462]

@@muhammedsabrisirin5324 You might check out Hayes' book on Conditional Process modeling. That's where I learned everything I know. Cheers! www.amazon.com/Introduction-Mediation-Moderation-Conditional-Analysis/dp/1462549039

[@muhammedsabrisirin5324]

Dear Mike i have bought book and looked Fundamentals but i have not seen my question's answers. İf you mind, i would like to send output to you? Could you look at it?

[@chrischen9637]

Thank you so much for these videos!! Question: If I have an additional mediator between anxiety and depression in the example you gave, do I simply put the additional mediator into the meditator(s) box, using the same model #? Or is there a different model # for a two mediator (with moderation) model? Thank you!

[@mikecrowson2462]

Hi Chris. I just saw your post. I've never had occasion to do what you are asking, but I just gave it a try using some data I had open. It looks like you can add in parallel mediators by including multiple mediators in the mediators box and then test for the conditional indirect effects involving those mediators. Best wishes.

[@ghareebawaam118]

its very nice but when i do the same its not gonna sow data foe visualization why it is so ?

[@mikecrowson2462]

Hi there. Unfortunately, there is no mechanism in Process to print out diagrams. The diagram I created was done using Powerpoint. I believe that the jamovi program might have the capability to draw out a diagram for you, but I haven't spent a whole lot of time on moderated mediation using that program. Cheers!

[@renee1995]

Thank you so much! I have one question though, how would it work if there would be an extra variable, specifically, one that is affected by depression? For example, happiness (in the case that it is not affected by any of the other variables in the model). Could you add that in PROCESS as well?

[@mikecrowson2462]

Hi Renee, thanks for your question. If you have a variable affected by depression, then it sounds like you have a serial mediation model (e.g., X-->M1-->M2-->Y) that you are proposing. Hayes' process macro (template #6; see www.personal.psu.edu/jxb14/M554/specreg/templates.pdf ) allows you to test for serial mediation. However, if you are asking whether you can test for moderation of serial mediation, then I don't believe I've seen a template that addresses that question. Hope this helps!

[@tigerwoods2067]

In model 58 and 59, I transfer continue moderator to order/rank variable, and setup "W" as "Multicategorical". After analyzing, I saw "Index of moderated medication (difference between conditional indirect effects)" in final table. Can model 58 and 59 do MoMe analysis? Could you tell me why, thank you very much!

[@ahsanatu]

Hi Mike, Thank you for the video tutorial. I have one question. Using PROCESS macro, can, and how can we calculate the change or increase in indirect effect of X on Y with 1SD increase in X at the high value of moderator via mediator? Other words, can we measure change in Y with the 1SD increase in X via mediator at high level of moderator?

[@itratbatool9907]

Sorry, i'm a beginner and wasn't able to understand what is ''null of zero''? Would it be possible for someone to please explain me this?

[@mikecrowson2462]

The null hypothesis when testing mediation (i.e., indirect) effects is the same as the typical null hypothesis in other tests: that is, the population effect is 0 (null). If the null of 0 falls between the lower and upper bound of a confidence interval then you maintain the null that the population indirect effect is 0, whereas if 0 falls outside the lower and upper bound of an interval, you reject the null and infer the population indirect effect is not 0 (i.e., statistically significant). The same logic is applied to the confidence interval associated with the Index of Moderated Mediation (IMM). The null in this case is that the IMM=0 (meaning no evidence of significant moderation of a mediated effect), and if 0 falls within the confidence interval for IMM, then this is interpreted to mean there is no evidence of significant moderation of that mediated effect). If 0 falls outside the confidence interval, then it is an indication that the IMM is considered significant, in which case you interpret this to mean that the indirect effect is conditioned on the moderating variable. Hope this helps! cheers!

[@Oisin8]

I have been trying to run an analysis using process model 84 (also moderated mediation) however when I standardize my variables , the significance of the results changes quite a lot from the unstandardized variables. I ran a correlation between unstandardized and standardized variables to ensure they all correlated to 1. Any ideas why this could be? When I used process model 6 (mediation) I get the same significance when using either standardized/ unstandardized variables? So I wonder if it could be any setting with options for model 84? Would really appreciate if anyone knows how to help?

[@ajungagung]

hi mike i just wonder, what if there are different results between -1SD, the mean, and +1SD of the moderator? on my case, the value of lower and upper CI of -1SD is include 0 which mean is not significant, yet, on the mean and and +1SD i got significant in which there's no 0 included there, please reply my comment

[@yingzhu552]

hi, may I ask a question please? In my output, the p-value for "Int_1" > 0.001, indicating insignificant moderation. However, in "Conditional effects of the focal predictor at values of the moderator(s)" section, the p-value in the first row is smaller than 0.001, which means that the moderator is significant when it's at a low level(?). So, should I stop referring to this section ("Conditional effects of the focal predictor at values of the moderator(s)") if I got an insignificant "Int_1" in the beginning? Or not?

[@mikecrowson2462]

Hi Zhu, you stated above that the p-value for the interaction term was >.001 (indicating the moderation effect is not significant). If you are getting a p-value in the output of .001 or less, typically this is taken as an indication of statistical significance. Hope this helps.

[@PerformanceTezek]

Thanks for sharing. But it can help that strengthen your explanation less reading especially in beginning.

[@foadsf]

Thanks a lot for the great tutorial. It would be also great if you could also make tutorials for PROCESS implementations in Python and R. I have listed them all here in this Tweet: twitter.com/fsfarimani/status/1230628290689368064?s=20 not everyone has the luxury to pay for SPSS. And doing the analysis in Python, R or even LibreOffice Calc would really help.

[@mikecrowson2462]

Dear Foad, I'll see what I can do on how to perform the same analyses using more open source software. I've run across a Shiny App version of Process before (but can't seem to relocate it). It's a web-based version of the program created using R (I believe). If I find it again I'll try to do something with it. However, a really great open-source program that I've been encouraging is jamovi (which is a pretty easy menu-based program that is built on R programming). The developers continue to add in new functions all the time. You can download it here: www.jamovi.org/download.html . They also have a community of contributors in terms of videos and other materials. I don't have a video on moderated mediation using jamovi but you CAN perform analyses involving moderated paths in path analysis using the MedMod module (here's a very little something I put together for you to see: drive.google.com/open?id=1zJ1q24SEDuwf84JrOxwZwTPqkIzqTD1f). I do have a video using a separate module under MedMod on moderated regression (in case you are interested): kzbin.info/www/bejne/m6vappprmZJgrJo (my apologies but the audio will not be as good as this was made before I improved the audio for my videos starting this summer). Finally if you are interested in other R videos (on regression, SEM, etc.) check out the following playlist: kzbin.info/aero/PLITf5JBUH0l6My-aSE4CnROnPS9D6WuI8 . Hope this helps! best wishes and thanks for visiting!

[@aymanshaa]

Thank you very much!