Non-parametric ANCOVA (Quade's) in SPSS
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- Опубликовано: 23 авг 2024
- This video explains step-by-step procedure to perform Non-parametric (Quade’s) ANCOVA in SPSS.
One of the vital assumptions of ANCOVA is that the residuals should be approximately normally distributed for each category of the independent variable. But what do we do if distributions in groups are non-Normal ?
In this case, we use Quade’s ANCOVA...
Quade’s ANCOVA is the used to adjust for covariates when you have a non-normal distribution.
While SPSS does not currently offer an explicit option for Quade's rank analysis of covariance, it can be done by following the steps explained in this Video...
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Thank you for the video. It was highly required. Well explanatory and detailed video. Keep it up.
I've been looking for the tutorial on ranked ANCOVA and here's the one! Thank you so much for making this video.
You are welcome... Glad that you found it helpful
Finally, someone explained how to do Quade's test in SPSS. However, it was not what I was expecting. I have heard that Quade's test can be used to compare correlations between two or more groups. For example, suppose a grouping variable sex and consider continuous variables such as weight, height, age, blood glucose, and so on. I want to compare, for each variable, the correlations for male and female. I appreciate it very much if you could explain how to do that using Quade's test. Thank you in advance
Very clear and simplified explanation. Thank you
Thank you so much 🙏💕
👩🎓 Thank you for making a very understandable and easy to follow video 👏 Thanks a lot 🙏
I am glad that you found it helpful.... Thank You and Best Wishes
Hi, thank you for the great tutorial! I was wondering, is it possible to look at the interaction with another variable with this analysis (like in a two-way ANOVA)? Thank you!
Thanks! i learned something new today and will implement this for my work project
Glad you found it helpful...
Thanks so much for this video! Do you know if it can be used for a categorial (dummy coded) covariate?
Thank you for the clear instructions. I was looking for the way to perform non-parametric one-way ANCOVA.
At the end of the video, you reminded us that "The assumptions made by Quade include that the distribution of any covariates is the same in each group, so the utility of the method is restricted to situations where groups are equivalent on any covariates."
However, the covariate (covariate-of-non-interest) was considered just because there were statistical differences in the covariate (age) among different independent groups. Thus, the distribution of the covariate (age) in each group was not the same. Is Quade's still valid in this case? Thank you very much.
I was wondering the same thing! I also used the Quade's as a non-parametric one-way ANCOVA, because my covariate (age) differed between groups. Did you get any clarification? Is Quade's still valid?
Thank you for the tutorial. When practice and follow all the step, the result does not show the last 3 column. What I supposed to do? Sorry for my bad English
I need one clarification here. In your example, after controlling the covariate, you found or showed Gender is not significant. Does it mean the covariate may act as confounder?
Great video, thank you for sharing. I wondered if and how this could be done for a repeated measures design. I have 3 time points (within measure) and 3 groups (between measure)?
Thank you very much for your help. I have a question. If I have two covariates, the analysis procedures are the same?
Yes absolutely... It would be the same procedure
Thank you for the video! Can you please advise, which post hoc test to use to make multiple pairwise comparisons after Quade's ANCOVA? I run Quade's ANCOVA the same way as in your video but I'm not sure if the classical Tukey test will work
Thank you so much!!!!!!!😊
Hi, thank you for your video and simple explanation! Can you tell me if I can use the residuals variable for Spearman correlation to run a quasi partial correlation?
I have three categorical variables and need to find out the pre and post-test effect. Also following non-parametric test as my sample size is very small. can I use the above method? I am getting negative values and means when calculating the difference. can i use quade's ?
E.g 3 cotogories, pre and post test , hypostesis : their is no difference of pre and post test for each category
Then, you may have to use Pre test scores as covariates across the three categorical variables.
Hello, i understand how i have to do in spss but I don't know how to interpret and describe de results of the table intersubject effects test. I do not know if I have to look at the corrected model (in the f and in the following, in what it says intersection or in the category of my table. Plese, can you help me? thanks
When writing up the results, you can simply report figures from the ANCOVA table as follows:
F(dfbetween, dfwithin)= F Value, p = significance
If p > 0.05, then there is no significant difference in mean values...
Sir , if you tell us some information about data , what we wanted to see what data we have , it would add more effectiveness in video 🙏🙏🙏
Very nice and well explained video. How would you interpret the power and effect size of the outcome? Since I can imagine that ranking the data would affect those values. Or do you prefer not report those since it may cause confusion? Many thanks!
Glad to know you found it helpful !!!
When writing up the results, you can simply report figures from the ANCOVA table as follows:
F(dfbetween, dfwithin)= F Value, p = significance
Good job😍
Thanks for your appreciation🙏
Dear Dr. Anis ur Rehman, thank you a lot for this very well explained video: I found it very useful! I am facing some issues in interpreting the results (table "Tests of Between-Subjects Effect"): should I look only to the F value or also to the signficance value? What does it mean that the significance of my “Corrected Model” is greater than 0,05? Why are the values of the corrected model and of the CODICE_ATN_N equal?
Thank you a lot for your help!
Dear Federica, Glad that you found it useful....
Yes you have to look at both F value as well as the p value.... When writing up the results, you can simply report figures from the ANCOVA table as follows:
F(dfbetween, dfwithin)= F Value, p = significance
If p > 0.05, then there is no significant difference in mean values...
how to adjust for stratum including covariance??
Does this work for multiple covariates? I have three covariates, should I include all three in the places you include your covariate in the video (so that the RES_1 contains all 3 covariates)?
Thanks for this, I don't know how I'd submit my paper without this! I found the instructions by SPSS tutorials online and it was hard to follow as I'm not very good at statistics. A lot of us are statistics noobs, simple explanations of p values, effect size and power and why you'd use them are helpful!
Yes, it works for multiple covariates... But you have to take them one by one. Please note that RES_1 has only one covariate (EK)
@@BizzPedia Thanks for the video....a query while running with multiple covariates. Do we repeat all above 3 steps for each covariate one by one when we have multiple covariates ?
@@pabgrg3199 you are welcome dear...
Yes, your have to repeat all 3 steps one by one for each covariate
@@BizzPedia Wow. Thank you so much for the detailed explanation, Dr. Anis. I were looking for Non parametric ANCOVA test where I can use One IV with two Covariates. And presumably, Quades' test may work better!
@@ANKITGUPTA-rw2gf Glad you found it helpful... Have a good day
Nice video.
Is this method also applicable for a MANCOVA instead of a ANCOVA?
I don't think this method will apply for MANCOVA.... You could check if your data have a ranking. In terms of levels of measurement, non-parametric methods result in ordinal data. You may analyze your data with Kruskal-Wallis test.
Thank you for this video. Can you use continuous variables to run Quade’s test?
Glad you found it helpful Yesenia...
Yes, you can use it with continuous variables.
Business Manageopedia Thank you for your reply!
I thought i could use this test. Unfortunately my covariate seems fixed.. Is there another non-parametric test i could use? Because this is the only assumption that is being violated
You can use Kruskal-Wallis test.
@@BizzPedia Thank you for your quick reply! But what would you do with your covariates with a kruskal-wallis test?
@@Jer0ne Unfortunately, Kruskal Wallis test doesn't offer any consideration for a covariate. I think R can offer a solution for your case, as it has options for non parametric ANCOVA...
YOUR CLASSICAL IS VERY VERY DISTURBING, i DONT KNOW HOW CAN i TELL YOU. BUT YOU DO GOOD JOB IN THE VIDEO/TEACHING ASPECT GO AHEAD