This just made my data analysis for my thesis 100000x easier. Bless your soul sir, bless your SOUL.

i have watched a number of the videos and Todd explains these issues incredibly well. thank you

this is the only channel that i go-to for both entertainment and help with my school assignments

The video helped to explain why interaction effects are important. It is interesting that you can have the two levels of the independent variable not significant but the interaction effect is significant.

This video did a good job explaining how the effect of multiple variable. I will be incorporating both the main and the interaction effect into my paper.

Explains every step in an understandable, clear manner. Very helpful. Thank you!

Dear Sir, your video has helped me more than any others to carry out my research. God keep you in a good health and healthy life. More videos on ANOVA, manova.

This was very helpful to see the interaction effect that would have been missed otherwise.

Thanks Dr. Grande, your video was super helpful!

Thank you Dr. Grande, you have helped me a lot.

Thank you, helped me a lot!

Great breakdown of ANOVA's value as a statistical test.

My Biostatistics professor at UNMC has recommended your videos for both Biostatistics I & Biostatistics II.

Thank you. very helpful

Thank you very much for this video! I want to test an interaction between a categorical predictor (3 levels) and a continuous predictor. This would be ANCOVA, but I don't know how to interpret the results. Can I do it the same way you do it here?

Amazingly helpful

I have a question that after running 2 ways ANOVA and we got a significant interaction effect. Then how can we do the post hoc of that interaction to present them in the form of letters above our graph?

Dear Todd, thank you very much for this great video. However, I habe a question regarding group comparisons. For instance, If I would establish a hypothesis that for the individual program, males have higher symptons than females. Is it possible to test this? Or do I have to conduct t-tests for that?

sir i love you so much thank you 😭💜

Thanks doc you are great

Thank you Dr Grande for making this video. Is it also true that by using ANOVA the risk of making a type 1 error is reduced?

thanks very much!!!

just great Todd thank you

this helped me so much THANK YOUUUU

I'm going to have to watch this several more times....

Helpful, thank you!

Hi, Great video. However, how do we test interactions if the assumptions for ANOVA are not met? Is there any nonparametric equivalence for it? Is this possible to be done in SPSS? Thanks!!

Can I ask please, if we found statistically significant interaction effect between two variables, how does that affect our decision to include them in a regression model?! Do we adjust for them? Do we remove them?

Thanks for your helpful video! I have the same result with my data. I wonder whether it is possible to have insignificant main effect and significant interaction effect. How do we intepret the results? Because at this time, the effect of indedent variable is not significant in both groups of the moderator. So, is the result of significant moderating efffect still meaningful for implications? Please help!

Thank you for the video, could you also say what the error displayed in the test of between subjects table indicates?

What if we find no statistical difference for all of the effects (main & interaction)? Do we have to report them and how do we do that? Thanks

THanks!

thank you

What if you have more than 3 variables? Do you just make combinations for all interactions? I noticed if you add more it changes 2 way interaction p-values.

thanks!

This is helpful but one that needs to be watched a few times

very helpfull

Hi, I'm so happy to see this video I was just thinking about doing that test, but I'm not sure I have enought people. I have +/- 50 people, on two dicotomus (yes no variable) and on continus (p.0 a 0,50)? Is it enought pr should I do like two t test or just the main effect of two-way anova without the interaction?

I have no idea why SPSS didn't report the significance for one independent variable and interactions between variables. I have conducted calculations step by step introduces in Your movie... :(

I always come to Dr Todd Grande when I have any confusion with my statistics

Hello, I very much appreciate your help with this as I am working on my dissertation and had a problem understanding this. I do have a question if you have the time and interest? If you are doing a 3 way anova (to account for two confounding variables -categorical-) and in the Test of Between Subjects Effects box the only significant result was your primary Independent variable (no other significant interactions), but in the independent variable (in this case, a confounding variable) section box further down their is a significant difference between the groups, such as gender, should you ignore this? (I'd presume so based on the video). The second question is whether I would report the interaction between the two independent variables that are really confounding variables, or should it only be the main effect between the independent variable (primarily tested) on the dependent variable? (I'd presume only significant main effects, ignoring the two confounding variables together?) Thank you very much, I genuinely appreciate your time and if I can help your channel in some way I'd be happy to!

great explanation !i appreciate it,thanks! can i have this data please?

Hi! I need help with reporting the results. In my study, Path a, b, c and C' all are significant in the Hayes mediation model 4. However, the effect size of path b (M on Y) is .08 , path c (X on Y is .05 ) and path a (X on M is .3)Also the c' has increased instead of decreasing or being zero. I had earlier reported The results showed a significant indirect effect of X on Y via M (b= -.1267, 95% BCa CI [-.1997, -.0556]). Indirect effect of X on Y Effect Boot SE BootLLCI BootULCI M.COM -.1267 .0357 -.2007 -.0587 Normal theory tests for indirect effect Effect se Z p -.1267 .0340 -3.7263 .0002 The moderation effect at three levels of M were also significant. F (3, 479) = 17.28, p < 0.001, R2= .0977), but with a very small effect size. At all three levels of M, there was a significant relationship between X and Y . For example, at low levels, (b= .29, t (479) = 5.06, p

Very poor