You are the bestttt!! i have my stats assessment tomorrow and i've been crying trying to wrap my mind around all of the analysis and reporting expected for us to do. Thank you sooo much 🥺
Your video was super helpful. Please make videos on moderation analysis using two categorical variables. This will help us understand why effect coding is necessary instead of dummy coding. What makes your videos stand out is the addition of APA reporting. Keep it up.
Thank you for your video it's been really helpful. I have been looking for a published article that reports a moderation analysis using MACRO PROCESS, would you have any example?
Hellou. I am currently working on data that explores the link between negative childhood experiences, the Dark Triad and alcohol consumption. In a linear regression, I found that both negative childhood experiences and the Dark Triad predict alcohol consumption. However, in the analysis using PROCESS, I found that the direct relationships between these variables were no longer significant. Instead, I observed a moderating effect, with negative childhood experiences acting as a moderator between the Dark Triad and alcohol consumption, supporting my hypothesis. I would be interested in your views on these differences in results and perhaps some advice on how to better understand and interpret these results. Could you please explain to me why these differences between the results of the linear regression and PROCESS analysis might occur? Could it be related to the moderation effect that I have observed? Thank you for your time and help.
@@AppliedStats Thank you so much! However, I have created dummy variables and, when I send them to the covariates box, after running the macro, it gives an error saying "one of your model variables exhibits no variation (its a constant)". Do you know what should I do then?
Hi there, I used the same options as you but I'm not seeing the "Conditional effects of the focal predictor at values of the moderator(s)" section. Does it perhaps only show up when the interaction effect is significant?
In order to obtain results even when the interaction is not significant, select the "Always" option located under "Probe Interactions" in the Options window.
Hello, in your video and in everyone elses the output (model summary) gives the following: R, Rsq, MSE, F, df1, df2, P. But when i do the exact same steps i get the following model summary: -2LL, ModelLL, df, P, McFadden, Coxsnell, Nagelkrk. How is this possible and how do i change it? Thankyou.
If your outcome variable or mediator is binary (such as yes/no or success/failure), Process Macro automatically performs a logistic regression analysis. That's why you see outputs like -2LL, ModelLL, and McFadden's R-squared, which are specific to logistic regression. In this video, I used continuous outcome and mediator variables, for which the macro performs linear regression by default.
I have 'gender' as my moderation variable. Can I just put it in the Moderator variable W, or do I need to change my variable beforehand? The value of gender is: male = 1 and female is 2.
Has anyone encountered the problem when Process Macro doesn't want to produce a "Conditional effect of the focal predictor at values" table? I suspect it's because my interaction turned out to be not significant, and it seems like the new Process Macro version doesn't produce this plot by default if p-value is above 0.05. Does anyone know what to do in this case? Cuz I still have to report the precise numbers, even though interaction is insignificant, but I simply don't have them 🥲 Please help 🥲 (great video though, thank you!)
In order to obtain results even when the interaction is not significant, select the "Always" option located under "Probe Interactions" in the option window.
@@naseerajasmir1234 In order to obtain results even when the interaction is not significant, select the "Always" option located under "Probe Interactions" in the option window.
You are the bestttt!! i have my stats assessment tomorrow and i've been crying trying to wrap my mind around all of the analysis and reporting expected for us to do. Thank you sooo much 🥺
💯 I haven't seen any video better than this on Moderation Analysis. Thanks ❤
Here's to your 100th subscriber. 💯 Amazing Video. Thank you for making it clearer. Bravo 👏👏
Your video was super helpful. Please make videos on moderation analysis using two categorical variables. This will help us understand why effect coding is necessary instead of dummy coding. What makes your videos stand out is the addition of APA reporting. Keep it up.
ua-cam.com/video/-030VJ-jidc/v-deo.htmlsi=jldZbd7ak1DyzPy4
Brilliant video. Thanks
Such a great video, thanks!
Sir we need to mention that Hayes 2022 reference under the graph also? Secondly do we need to report ULCI and LLCI results in the write up as well?
Everything I report in the video is crucial for psychological research, though it may differ in your specific field of study.
how about to read the graph if the case there is 2 independent, 1 dependent and 1 moderator variable?
Super easy to follow
Thank you for your video it's been really helpful. I have been looking for a published article that reports a moderation analysis using MACRO PROCESS, would you have any example?
how about using these keywords? scholar.google.com/scholar?as_ylo=2020&q=%22moderation%22+%2B+%22process+macro%22+%2B+spss+&hl=en&as_sdt=0,5
Hellou. I am currently working on data that explores the link between negative childhood experiences, the Dark Triad and alcohol consumption. In a linear regression, I found that both negative childhood experiences and the Dark Triad predict alcohol consumption. However, in the analysis using PROCESS, I found that the direct relationships between these variables were no longer significant. Instead, I observed a moderating effect, with negative childhood experiences acting as a moderator between the Dark Triad and alcohol consumption, supporting my hypothesis.
I would be interested in your views on these differences in results and perhaps some advice on how to better understand and interpret these results. Could you please explain to me why these differences between the results of the linear regression and PROCESS analysis might occur? Could it be related to the moderation effect that I have observed?
Thank you for your time and help.
Hi, thank you so much. It was very helpful. However, I wonder how could you control for control variables. Thank you so much
Just need to send them to the "covariates" box
@@AppliedStats Thank you so much! However, I have created dummy variables and, when I send them to the covariates box, after running the macro, it gives an error saying "one of your model variables exhibits no variation (its a constant)". Do you know what should I do then?
@@cristinamorillo7259 there is a problem with your dummy variable
Thanks.. do you have video for model 2?
no. [you just need to send your second moderator to the "moderator variable Z" box.]
Thanks, that helps for sure
Thanks a lot, easy for learners to follow. 😄
Hi there, I used the same options as you but I'm not seeing the "Conditional effects of the focal predictor at values of the moderator(s)" section. Does it perhaps only show up when the interaction effect is significant?
In order to obtain results even when the interaction is not significant, select the "Always" option located under "Probe Interactions" in the Options window.
What does the intersection mean? Is it a threshold, and what are the implications before and after the intersection?
In most cases, it is not the intersection of the lines that is important, but rather the slope of the lines
Hello, in your video and in everyone elses the output (model summary) gives the following: R, Rsq, MSE, F, df1, df2, P. But when i do the exact same steps i get the following model summary: -2LL, ModelLL, df, P, McFadden, Coxsnell, Nagelkrk. How is this possible and how do i change it?
Thankyou.
If your outcome variable or mediator is binary (such as yes/no or success/failure), Process Macro automatically performs a logistic regression analysis. That's why you see outputs like -2LL, ModelLL, and McFadden's R-squared, which are specific to logistic regression. In this video, I used continuous outcome and mediator variables, for which the macro performs linear regression by default.
Do you have downloads of the word APA file?
Hi, do we report the R square change or not?
Reporting would not hurt
I have 'gender' as my moderation variable. Can I just put it in the Moderator variable W, or do I need to change my variable beforehand? The value of gender is: male = 1 and female is 2.
How about watching my new video on binary moderators: ua-cam.com/video/AIKiV30kX30/v-deo.htmlsi=1NiqdwVfvJuU1esI
Where do we get beta value from?
To obtain standardized coefficients, click on Options and check the "Standardized Effects" option.
Where do we get B value from
B = coeff
Great, thank you
Has anyone encountered the problem when Process Macro doesn't want to produce a "Conditional effect of the focal predictor at values" table?
I suspect it's because my interaction turned out to be not significant, and it seems like the new Process Macro version doesn't produce this plot by default if p-value is above 0.05.
Does anyone know what to do in this case? Cuz I still have to report the precise numbers, even though interaction is insignificant, but I simply don't have them 🥲
Please help 🥲
(great video though, thank you!)
In order to obtain results even when the interaction is not significant, select the "Always" option located under "Probe Interactions" in the option window.
Ys i can't get conditional effect of the focal predictor at values table...pls help me sir
@@naseerajasmir1234 In order to obtain results even when the interaction is not significant, select the "Always" option located under "Probe Interactions" in the option window.