One-way ANCOVA on SPSS with assumption checks and write up (APA style)
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- Опубликовано: 15 июл 2024
- Learn how to complete a one-way ANCOVA on SPSS with assumption checks and how to report the results in APA style.
0:00 What is a one-way ANCOVA?
0:26 Setting up the data file
3:02 Checking the assumptions: normality, linearity, homogeneity of regression slopes
10:25 Running the ANCOVA and checking homogeneity of variance
11:33 Interpreting the results
12:49 Reporting the assumptions of the ANCOVA
18:48 Reporting the ANCOVA
Reference for the citation in the results:
Pallant, J. (2011) SPSS survival manual: A step by step guide to data analysis using the SPSS program. 4th Edition, Allen & Unwin, Berkshire.
Can I just say this has to be the most detailed breakdown of ANCOVA in SPSS and you went even further to demonstrate how to not just interpret but report it. You are really a superb educator! Thanks Doc!
Thank you!
What a legend you are! Straight to the point. No nonsense and I love it
Thanks Jeff, glad it helped!
Love this, helped with my 2-way ANCOVA analysis for my MSc Forensic Psych Thesis! hugs xx
Thanks Saumya, glad it helped!
Thank you for an outstanding video. I now have a much better understanding of how to do an ANCOVA.
Glad it helped!
Thank you, Dr. Robinson for the excellent tutorials. They are tremendously helpful.
Thanks, glad the videos are helping!
Well done! Very well explained, thank you so much!
Thanks Jennifer, glad it was helpful!
This was fantastic!
Thank you very much.
Thanks, glad it helped!
excellent tutorial! help a lot
Thanks, glad it helped!
David, thank you so much for this video. It would be great if you could tell us what to do if the assumptions are not met.
Hi, the test is usually considered quite robust to violations of normality, so these wouldn’t rule the test out, but violations could be acknowledged in your report. Re. the assumption that there’s a linear relationship between the DV and the covariate, if this is violated it can reduce the power of the test. However, again, this wouldn’t necessarily rule out running the test. In this case, you could consider removing the covariate, which would mean running an alternative test (e.g., a t-test) if there was only one covariate. If the assumption of homogeneity of regression slopes is violated, the test results may be misleading, so you may need to consider an alternative test. Regarding homogeneity of variance, you can adjust your alpha (e.g., from 0.05 to 0.01) to help account for violations. Hope that helps!
This video saved me !!!!!!!! I was so confused Before … and even made me laugh degrees of 3some !!!!
Glad it helped!
17:27, Thank you David
Glad I could help!
Hello Dr Robinson. Thanks for your videos, they are helping me a lot. I love how you include the assumptions and write up on them.
I have a challenge that maybe you can help me with. I am using a Repeated Measures Mancova with 4 factors, each one with 8 groups. I also included 3 covariates in the analysis. I discovered there was a significant difference between at least two groups in one of my interactions. I would like to apply a Pairwise comparison to compare separately the groups of my factors, but taking into consideration the interaction. How can I do that in SPSS? Thanks in advance.
Dear Dr. Robinson,
Thank you for the well constructed video! Was very helpful!
My question is: in case there is violation of the assumption of homogeneity of regression slopes and therefore interaction between IV*covariate, do you proceed directly to ANOVA? Is there a way to further investigate the relationship of covariate with each group of your IV separately?
Thank you in advance!
Hi Dr. Robinson, thank you for this helpful video. I have a question. How to present these results in a table for an article?
Which lines are we supposed to look at when checking the homogeneity of slopes?
Hi David, Thank you for the video and explanation. I have a question regarding the normality assumption and homogeneity of variance assumption. Do we need to only consider the outcome and independent variables for checking these assumptions or we need to add the covariate as well?
Hi, thanks for your question. I haven't seen any resources that they that the covariate has to be checked for these assumptions too.
Hi, David!
Thank You very much for such an insightful video!
But please, can You shortly explain when You are interpreting eta-squared and when partial eta-squared in SPSS? As I understood, SPSS automatically produces "partial eta-squared" in one-way ANOVA output, but actually it is simple eta-squared (this must not be misinterpreted). And when there are already another fixed factor (it's already factorial ANCOVA) then it is indeed partial eta-squared. Am I right? But when I have one-way ANCOVA (IV= group 1 and group 2; DV= post-pre intervention differences and pretest value as a covariate), then it is still only eta-squared?? And if the sample size is below 20, I should present omega eta-squared as an unbiased ES estimate?
Can You please give some clarity?
Thank You!
David can you help with calculation for sample size for ANCOVA
Hi David, am I allowed to add another categorical covariate to an ANCOVA?
For example, if I already have a numeric DV (stress level), a categorical IV (treatment) and a numeric covariate (age), is it ok to add a categorical covariate (gender) to this?
Will this still be a one-way ANCOVA and will the assumption of linearity still apply for this?
Hi,
Thanks for your question.
It's fine to have multiple covariates. It's more common for the covariate to be continuous, though many argue that it's fine to have categorical covariates, and that the assumption of linearity doesn't apply in this case: www.researchgate.net/post/Check-linearity-between-the-dependent-and-dummy-coded-variables
Hope that helps!
David.
Hi Dr. Robinson, why in my column in the table of 'Tests of between-subjects effects', I have not a number, but '9.208E-7', could you help me find the reason to solve this? There are missing data, and i took them out to run again but ended up with the same results. Thanks!
Hi David, I would like to ask a question which is not related to the topic of the video above. I just don't know how to contact you.. Aside from the comments section.
My question is in regards to the use of Kolmogorov vs Shapiro-Wilk test. How to know which one is best? or when to know which one to use? Can you make a video in regards to normality?
Thanks a lot!
Best regards,
Kim
Hi Kim,
Thanks for your question.
Generally speaking, researchers tend to use the Kolmogorov-Smirnov test with larger samples (n > 50) and use the Shapiro-Wilk test with smaller samples (n < 50).
Here's a reference: www.ncbi.nlm.nih.gov/pmc/articles/PMC6350423/#:~:text=The%20Shapiro%E2%80%93Wilk%20test%20is,taken%20from%20normal%20distributed%20population.
Hope that helps!
David.
Hi David. Do you have any dataset for one-way ancova? or where can i find data set for this from true population? thanks!
Hi Lowie, there's a downloadable dataset here that you could use: help.xlstat.com/s/article/ancova-analysis-in-excel-tutorial?language=en_US
Good one, please how can i get the pdf of that report you used please
Dr, if my pretest results are significant between the control and experimental group... should I run a ancova to control the pretest score and see how the post-test score would be?
an independent t-test showed significant difference in the pre test...
Hi, yes, ANCOVAs are often used to do just that.
@@DavidRobinsonPhD thank you very much Dr
Great explanation👍👍 buts it's crazy to me that, he has a landlines🤯🤣. Thanks for the video, though.
That's just to talk to people outside the building 😅
@David Robinson, PhD that makes more sense🤣🤣
Hi David, how can I run the test when I have gender instead of age? I will also want to make my pretest a covariate.
Hi Aina,
Thanks for your question. Could you let me know what your IV(s), DV(s), and covariate(s) are?
Best,
David.
@@DavidRobinsonPhD Hi David, thanks for very informative videos and really making data analysis relatively easier.When reporting the results, you state that the marginal means were similar (I can appreciate that visually since its 5.82 vs 5.83). Is this based on the p value suggesting there was not a significant effect of condition on cognitive scores? How can make a such a judgement statistically? Do I use contrasts or post hoc tests?
@@mwanganamubita9617 Hi Mwangana,
Thanks for your question.
Yes, it's based on the non-significant effect of condition on cognitive scores. Also, the partial eta squared value (.003) suggests a very weak effect. If you wanted to avoid using "similar", you could say something like, "...there was not a significant difference in cognitive test scores between the control [insert descriptive stats] and intervention [insert descriptive stats] conditions, [insert inferential stats]." Re. post-hoc tests, they're usually only used when your IV has three or more levels.
Hope that helps!
David.
@@DavidRobinsonPhD Many thanks for the clarification
@@DavidRobinsonPhD, Do you have a video on repeated measures Ancova or can you help me with how to report results of repeated measures Ancova with dependent variable at two levels (measured twice)? Warm regards