Multivariate Statistical Analysis Part 3: MANCOVA (with R Demonstration)

This is the 3rd part of my Multivariate Statistical Analysis video series on Multivariate Analysis of Covariance (MANCOVA). MANCOVA is a method for looking at if the means of the multiple outcome variables between each group (specified by the group variable) are statistically different while controlling for a covariate which can influence the outcome but is not of study interest.
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[@xiaoruyu4403]

Thank you for making these very informative videos. Looking forward to your next one on repeated measures! :)

[@cindywang8852]

Hi! Very helpful videos! I wonder if you could upload the rest of your videos?

[@jcftsgjc]

Please we want to see MANCOVA with the jmv package! Thank you

[@jyotsnarao2939]

Thank you so much for making this tutorial. I found it extremely helpful. Please can you show how to use MANOVA function in jmvcore package.

[@MeggyCroal]

i would like to see a video including MANCOVA package :-) Great video!

[@mpk52kevin]

Muchas gracias!

What should be done if we see violations of the assumptions? What could be alternative methods?

[@VladimirShatalov]

Thank you for the interesting lecture. It seems there are mistypes in the lines 72-73: not 'jmvcore' but 'jmv' is correct.

[@tilmojema4515]

it is a good topic but i suggest you to add mulitivariate probit regression model topic in your presentation

[@augustoanguita2487]

NICE CONTENT

[@mariatsapali392]

I am trying to add multiple covariates (n=6 covariates) in a MANCOVA model in R and I cannot find any guidance as how to go about it. My code using only one covariate is the following:
MANCOVAModel

[@yamengzhang9463]

So what's the actual difference between covariable and independent variable since they enter the formula in a same way.

[@gabrielasalgado5648]

Saw your video and tryed to use 'jmvcore' but din't recognize the function; with 'jmv' I made a MANCOVA :)

[@niiayiankrah7072]

Please I don't see the new video you uploaded.