Split-Plot ANOVA (Mixed-Design Two-Way Repeated Measures ANOVA) in SPSS
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- Опубликовано: 6 авг 2024
- This video demonstrates how conduct a Split-Plot ANOVA using SPSS (Mixed-Design, SPANOVA). The example is a two-way repeated measures analysis of variance with one within-subjects factor and one between-subjects factor. The assumptions for two-way repeated measures ANOVA, interaction effects, and main effects are reviewed.
Thank you for the breakdowns. It helps to better understand how each test is preformed.
Sir, just to let you know how valuable your videos are to me, I use your videos to prepare for all my statistics exams in my Ph.D course, including my PhD comprehensive exams which are 2 days away as of this writing
This video was a good refresher on how to read and understand the output for a two way repeated measures anova. It was broken down in a way that was easy to follow and understand.
I liked learning about the various ways to measure the differences within and between two groups. It extracts more data from which to work with and apply to research.
Understanding the process of an anova within a text can become tricky and confusing, but watching a video like this can make one understand the process a little bit better. It is interesting to me how you can break down all four distributions.
video is helpful in showing how to compare the various data comparing within subjects to that of between subjects, especially how it gives explanation of certain concepts like factor interaction.
This is a great way to demonstrate the two-way repeated measures analysis of variance. I like the steps but this requires persistent practice.
Since you say that I cannot really be sure that there is a main effect for time, How would I report this result? Would I state that there was a main effect for time but that the interaction effect specified that this was only so for the CBT group? Thank you for any explanation in this regard. I find your videos incredibly helpful and clear!
thank you! amazingly helpful
I never really thought about the possibility of using ANOVA with independent variables between subjects versus independent variables within subjects. This is a new concept for me. I would like to try it out myself to see if I understand how to actually go through the motions and achieve success in doing so.
Oh man YOU ARE THE BEST!!!!!!!!! THANK YOU!!!!
So for the comment made at 10:52 how can we determine that? t-test?
It was very helpful! thanks!
You're welcome, thanks for watching!
is there gonna be a part 2 on how to proceed? please do!
thank you so much :D
Thank you it was great.
thanks for this very comprehensive video. I hope you will do another video showing how to run a post-hoc test for this type of analysis. Will it be right if I conduct an aligned rank test for this same kind of data but with the dependent variables being on the ordinal scale?
You can do the normality test with the residuals. In that way, you use all your values to do the shapiro wilk instead of dividing all the data into subgroups. Normally it's hard to detect normality with a small number of subjects.
Once if it doesn't holds normality what can we do ?
Dear Dr. Grande, congratulations in your great explanation. I would like to know if there is an easy way to present the graphs with a hint to the reader about the variability of the results. SPSS does give us an "estimated SE", but it does not plot it in the graph. Do you know any way to present data, or should I just present the graph without error bars?
Hi, your video is awesome. I want to ask you something, is possible to use this procedure with two factors? or, do I need to use another procedure?
Thanks!
what should i do if i have three dimensions of dependent variable. that means 3 pretests and 3 post tests
Hi, thank you for sharing this video. i am now more knowledgeable should i come across a setting where i need to apply the information
Awesome Video Dr. Todd, Could you please help me suggesting a statistical test for my research project. I have two group, assessed on two scales (before, after and follow-up). the data is ratio and demographic is categorical.
Thanks you for sharing your useful video. I am wondering how we should consider about other related source of variance in this design like age, weight… of participants? Thanks in advance for your reply.
That is a great question Far. I would like to see an example of this as well.
Hi Dr. Thank you first of all, however, i was wondering how can i just compare the effects of two of three groups (between-subject factors) on a within-subjects variable with pre and post test. since, if i have three methods that was typed into variable view with Method A=1, Method B=2 and Mehtod C=3. in this case, i also wanna identify what the difference between A and B, A and C, C and B. So if i drag the categorical varible to the Between-subjects factor that still contain those three methods, Right?
Could you make a video on post-hoc contrasts etc pls?
I'm not sure this is a split plot ANOVA. Correct me if I'm wrong, but isn't a split plot design one that uses two or more IVs? The classic example being from agriculture, with the experimenter wanting to see if irrigation (factor A with X levels) and fertiliser (factor B with Y levels) have an effect on crop yield (the DV). In this example, you appear to have one IV with two levels (treatment), and two DVs (pretest posttest). I understand that you enter these into the calculation as two levels of one factor, but I'm still confused about whether this is indeed a split plot ANOVA.
I feel like I would be lost if I did not have a step-by-step like this.
I agree, thankfully he breaks the process down for us. I becomes quite confusing with moving the variable, post test, etc over to the different boxes.
Krystle, you are correct. This video helps a lot by guiding us step-by-step.
I agree, I was rather confused about the Split-Plot ANOVA overall until he went through the procedure step by step. It's been really helpful for the research proposal
I was wondering how you would measure this when the dataset is rotated 90 degrees, so that every participant has two rows (post and pre)
you have to restructure the dataset
My main effect is significant but my interaction effect is not how can I proceed?