Multinominal logistic regression, Part 1: Introduction

[@Robin-zc2iw]

I'm doing a master's program in the US and my professor just explained this concept and I was so confused. Today's my test and this video makes my understanding of MN logistic regression so much better than it was. Thank you!

[@kaynkayn9870]

"Today's my test" - certified uni student moment

[@f.181]

Thank you very much for the excellent presentation. Very good video!
I have a question. At 13:37: shouldn't it be "The odds of being *unemployed* rather than in employment are 42% lower for women than for men"?

[@asadyare3268]

You are right.

[@tatianabarcenasbarreto6967]

Thanks for sharing this valuable knowledge with your clear and fantastic explanations.

[@Sanjeevpudasaini]

Thank you so much for such a good explanation!

[@KayYesYouTuber]

Good explanation of multinomial logistic regression.

[@prempant6428]

What's the explanation for that equation on slide 13:26 ? The logit scale which is used first is ln(x/(1-x)) = y, if I am not wrong so x = e^y / (1 + e^y), you say that you've used the odd scale values but you used the logit scale values, during the calculation of the percentages ?

[@KyambaddeFrancis-ih8uk]

Thanks for the presentation, which values of x did you use

[@bismarkanloadey289]

hello, what if, instead of the dependent variable being more than 2, you have the explanatory variable rather to be more than 2. example; how sitting technique (upright, bent and curled) impacts the shape of the spinal cord. can you help with the impact model that'll be ideal for this analysis?

[@clausvind8010]

The sliste at arounnd 13:22 have the same text for both bullets: I believe the second bullet should read "The odds of being unemployed rather than in employment are 42% lower for women than for men"

[@clausvind8010]

slide not sliste

[@samnangum2750]

Thank for sharing Dr

[@dentoda]

Mlogit depvar indepvar, rrr gives OR output instead of coefficients

[@jakobforslin6301]

Thank you very much!

[@mdahsanul]

Thank you.

[@kaushikjayaram8556]

Thanks for sharing

[@shashidharchavan3895]

@time line 13.23 the second interpretation should be unemployment rather than in employment.

[@JiyongKim-et9sw]

Thanks !

[@babaabba9348]

Mycket bra!

[@drisselghoufi6728]

Thank you🙏