Hello! Could you please tell me if i have to order my data like yours in this video in order to be able to put my variables in the cells of the Bayesian Repeated Measures Anova ? Because i'm studying the link between moral injury and sense of agency and i have 2 variables (or columns) ; one named "Memory" with two levels "Neutral" vs "Moral injury" and the variable "Condition" with two levels named "Voluntary" and "Unvoluntary". I also have a column named "Z-scores" with the z-scores of my participants because they had to give a number between 0 and 1000 to measure their sense of agency so I need to ensure that those results are normalized. However, when I go to the Bayesian Repeated Measures menu, nothing happens, I only see the variables "Condition" (categorical variable), "Memory" (also categorical), "Participants" (categorical) and "Z-scores" (numerical). Do I have to have only one lign per participant (I have 14 people in total) and then variables called "Moral Injury-Voluntary", "Moral Injury-Unvoluntary", "Neutral-Voluntary" and "Neutral-Unvoluntary" ? Thank you!
This video is a tutorial for the frequentist/classical analysis for ANOVA. Bayesian ANOVAs are different and set up differently. I don’t do Bayesian stats, so I can’t tell you how to set up your data, sorry!
Hi, thanks for your tutorial! I have a question: I have a continuous independent variable (individual scores, there’s only one score for each participant), and I want to know the effects of the scores and the interaction effects of the scores by other variables (two different within-subject variables, each has two levels), can I input the scores as the Covariate for the repeat measures ANOVA analysis?
Hello, first, thank you very much for the tutorial, it is super helpful. I do have one question however: you are stating at minute 13:29 "if the p value is below your alpha you have a problem with sphericity". What is or where is the alpha in the given table, I do not manage to follow up in order to be able to compare the p value and alpha. Thank you!
Ah, good question. So you have options for the assumption alpha. You can use your basic alpha of .05, or you can do a more conservative value., like .01 or .001. Choosing a more conservative value means you are assuming the data is robust to a violation of the assumption, in this case sphericity. I usually teach a conservative .001 alpha, because I know I have really violated the assumption if the resulting p-value is more extreme than that. JASP uses a built-in ,05 and will flag assumption checks that are below that with a Note below the table.
Thank you for this great video! I have a question, if you had two different groups (experimental&control), with the same data, and Noise Level would have turned out significant (same as here), where can you see in the repeated ANOVA, which group performed better? Would I see that in the simple main effects? Thanks for your help!
You can't do post hocs in the Repeated measures modules in JASP for within subject variables. So I would just do a series of paired samples t-tests and adjust your alpha with a simple Bonferroni correction.
Hi, thanks for this video. It helps me a lot, but I still have a question (btw, i'm belgian so french native speaker and maybe I didn't understand everything). So, for my thesis, I have to do a repeated measures ANOVA. And my datas are randomised. I have to know if there are an order effect or not (Variable : Condition 1 (O then M) - 2 (M then O)). The name of "RM factor 1" is "nursing home types"; with "level 1" = "CCNH" and "level 2" = "CNH". My question is: to know if there are an order effect or not, do I have to put the variable "Condition" in "Between Subject Factors" ? Hope my question is clear and that you may help me. Have a nice day!
Hi--from what I can gather from your description, to see if you have any order effects, yes you'll input your Condition variable in the Between-subjects box. This will tell you whether your counterbalancing was effective or not. You're looking for a null effect for that one specifically; that way you can rule our any order effects. Cheers!
I wish you were my professor. You explain it perfectly . Thank you !!
Can i ask for the problem and dataset?
Hello! Could you please tell me if i have to order my data like yours in this video in order to be able to put my variables in the cells of the Bayesian Repeated Measures Anova ? Because i'm studying the link between moral injury and sense of agency and i have 2 variables (or columns) ; one named "Memory" with two levels "Neutral" vs "Moral injury" and the variable "Condition" with two levels named "Voluntary" and "Unvoluntary". I also have a column named "Z-scores" with the z-scores of my participants because they had to give a number between 0 and 1000 to measure their sense of agency so I need to ensure that those results are normalized. However, when I go to the Bayesian Repeated Measures menu, nothing happens, I only see the variables "Condition" (categorical variable), "Memory" (also categorical), "Participants" (categorical) and "Z-scores" (numerical). Do I have to have only one lign per participant (I have 14 people in total) and then variables called "Moral Injury-Voluntary", "Moral Injury-Unvoluntary", "Neutral-Voluntary" and "Neutral-Unvoluntary" ? Thank you!
This video is a tutorial for the frequentist/classical analysis for ANOVA. Bayesian ANOVAs are different and set up differently. I don’t do Bayesian stats, so I can’t tell you how to set up your data, sorry!
You explained everything so well and clearly that I understood everything with my poor knowledge of English. Thank you!
came here to study, why do I hear Childe Snezhnaya talking 😭. Thank you so much for this!
Hey, the link to the data doesn't seem to work.
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The requested URL was not found on this server.
Aww bummer! Thanks for letting me know
Hi, thanks for your tutorial! I have a question: I have a continuous independent variable (individual scores, there’s only one score for each participant), and I want to know the effects of the scores and the interaction effects of the scores by other variables (two different within-subject variables, each has two levels), can I input the scores as the Covariate for the repeat measures ANOVA analysis?
From your description, yes, that sounds like it would be good and possible
@@AlexanderSwan okay, thank you!
Hello, first, thank you very much for the tutorial, it is super helpful. I do have one question however: you are stating at minute 13:29 "if the p value is below your alpha you have a problem with sphericity". What is or where is the alpha in the given table, I do not manage to follow up in order to be able to compare the p value and alpha. Thank you!
Ah, good question. So you have options for the assumption alpha. You can use your basic alpha of .05, or you can do a more conservative value., like .01 or .001. Choosing a more conservative value means you are assuming the data is robust to a violation of the assumption, in this case sphericity. I usually teach a conservative .001 alpha, because I know I have really violated the assumption if the resulting p-value is more extreme than that. JASP uses a built-in ,05 and will flag assumption checks that are below that with a Note below the table.
Thank you for this great video! I have a question, if you had two different groups (experimental&control), with the same data, and Noise Level would have turned out significant (same as here), where can you see in the repeated ANOVA, which group performed better? Would I see that in the simple main effects? Thanks for your help!
You can't do post hocs in the Repeated measures modules in JASP for within subject variables. So I would just do a series of paired samples t-tests and adjust your alpha with a simple Bonferroni correction.
can you show us the video with covariates? thank you
I have a JASP ANCOVA video here: JASP 0.14 Tutorial: Analysis of Covariance (ANCOVA) (Episode 26)
ruclips.net/video/kCOHz9WgLBQ/видео.html
Hi, thanks for this video. It helps me a lot, but I still have a question (btw, i'm belgian so french native speaker and maybe I didn't understand everything).
So, for my thesis, I have to do a repeated measures ANOVA. And my datas are randomised. I have to know if there are an order effect or not (Variable : Condition 1 (O then M) - 2 (M then O)).
The name of "RM factor 1" is "nursing home types"; with "level 1" = "CCNH" and "level 2" = "CNH".
My question is: to know if there are an order effect or not, do I have to put the variable "Condition" in "Between Subject Factors" ?
Hope my question is clear and that you may help me. Have a nice day!
Hi--from what I can gather from your description, to see if you have any order effects, yes you'll input your Condition variable in the Between-subjects box. This will tell you whether your counterbalancing was effective or not. You're looking for a null effect for that one specifically; that way you can rule our any order effects.
Cheers!
@@AlexanderSwan Great, thanks a lot!
Can you please help me? you only use "scale" variables??
Scale in this context means "continuous" variables
Please any assistance on how to use JASP RCBD?
I'm sorry, I do not know what RCBD means?
@@AlexanderSwan Randomized Complete Block Design in ANOVA
@@AwuduAbubakari ok, I need more information. Please send me an email -- you can find that on my About page
@@AlexanderSwan I have been trying to get your email but to no avail.
@@AwuduAbubakari if you go to the Contacts page on my website, it's there