Thanks very much for detailed lecture, It will help me alot be blessed. You made it for stranger , the flood gate of God Blessing will fall upon your life.
Thank you a lot, this is really detailed and helpful. What about latent variables and the process function? I've been trying to figure it out on my own but it's not working.
Hi, thank for your kind words. Glad to be useful. I could be wrong, but as I know, PROCESS can not handle latent variables. PROCESS deals with variables with an aggregated format (e.g., the mean of a few items). You might need to use Mplus or some other R packages to deal with latent variables. Unfortunately, I have a limited understanding of latent variables and thus probably can not be helpful here. If the measure is just continuous (e.g., Likert scale measures), a simple mean of items can be used to test mediation model, IF you do NOT have specific reasons why you need to add latent structures to mediation models.
Thank you very much for this wonderful tutorial! My IV has 5 categories and my W has 3 categories. How do I specify them as multicategorical in R? (I know how to do this in SPSS, but am trying to replicate my results in R). Thank you again!
If your IV has 5 categories and these categories cannot "approximately" be considered as "somewhat" linear, I personally do not know how to do it in SPSS PROCESS (I have never done it myself). When checking online, I found a paper by Hayes (the PROCESS author) on this: quantpsy.org/pubs/hayes_preacher_2014.pdf. The reason I focus on PROCESS is that, if PROCESS can be used to handle this situation, the PROCESS in R and SPSS should generate the same result. Hope my comment helps.
When I do this process Model 7 with my SPSS, I got a positive sign for my moderator (w) and negative sign for Int_1 . I think this mean there is a positive moderation. I would like to know why I got negative sign for Int_1 ? Please help me
Hi, int_1 is the interaction, namely the moderation, not the moderator (i.e.,w), even though conceptually it is the moderator. You need to plot it, either via bar chart (if both X and w are categorical variables) orJohnson Neyman (for x and w, one categorical and one numerical; or even both are numerical). What you need to do is: (1) if int_1 is significant, reporting that the interaction effect is significant. (2) then, do the plot to tell your readers how the significant effect looks like. (Disclaimer: This is just my opinions and based on my best knowledge. Please verify by yourself. I do not take any responsibility if there is error, but I do my best already.)
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This is so detailed, hats off Tidy Data. Blessings bro.
My pleasure! Happy to be useful :)
Thanks very much for detailed lecture, It will help me alot be blessed. You made it for stranger , the flood gate of God Blessing will fall upon your life.
You are very welcome! Glad to be useful :)
Thank you a lot, this is really detailed and helpful. What about latent variables and the process function? I've been trying to figure it out on my own but it's not working.
Hi, thank for your kind words. Glad to be useful. I could be wrong, but as I know, PROCESS can not handle latent variables. PROCESS deals with variables with an aggregated format (e.g., the mean of a few items). You might need to use Mplus or some other R packages to deal with latent variables. Unfortunately, I have a limited understanding of latent variables and thus probably can not be helpful here. If the measure is just continuous (e.g., Likert scale measures), a simple mean of items can be used to test mediation model, IF you do NOT have specific reasons why you need to add latent structures to mediation models.
Thank you very much for this wonderful tutorial! My IV has 5 categories and my W has 3 categories. How do I specify them as multicategorical in R? (I know how to do this in SPSS, but am trying to replicate my results in R). Thank you again!
If your IV has 5 categories and these categories cannot "approximately" be considered as "somewhat" linear, I personally do not know how to do it in SPSS PROCESS (I have never done it myself). When checking online, I found a paper by Hayes (the PROCESS author) on this: quantpsy.org/pubs/hayes_preacher_2014.pdf. The reason I focus on PROCESS is that, if PROCESS can be used to handle this situation, the PROCESS in R and SPSS should generate the same result. Hope my comment helps.
When I do this process Model 7 with my SPSS, I got a positive sign for my moderator (w) and negative sign for Int_1 . I think this mean there is a positive moderation. I would like to know why I got negative sign for Int_1 ? Please help me
Hi, int_1 is the interaction, namely the moderation, not the moderator (i.e.,w), even though conceptually it is the moderator. You need to plot it, either via bar chart (if both X and w are categorical variables) orJohnson Neyman (for x and w, one categorical and one numerical; or even both are numerical).
What you need to do is: (1) if int_1 is significant, reporting that the interaction effect is significant. (2) then, do the plot to tell your readers how the significant effect looks like. (Disclaimer: This is just my opinions and based on my best knowledge. Please verify by yourself. I do not take any responsibility if there is error, but I do my best already.)