Multinominal logistic regression, Part 1: Introduction

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  • Опубліковано 29 лис 2024

КОМЕНТАРІ • 23

  • @Robin-zc2iw
    @Robin-zc2iw Рік тому +2

    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
      @kaynkayn9870 Рік тому

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

  • @f.181
    @f.181 3 роки тому +19

    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"?

  • @KayYesYouTuber
    @KayYesYouTuber Рік тому

    Good explanation of multinomial logistic regression.

  • @tatianabarcenasbarreto6967
    @tatianabarcenasbarreto6967 Рік тому

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

  • @KyambaddeFrancis-ih8uk
    @KyambaddeFrancis-ih8uk 6 місяців тому

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

  • @Sanjeevpudasaini
    @Sanjeevpudasaini 2 роки тому +2

    Thank you so much for such a good explanation!

  • @prempant6428
    @prempant6428 2 роки тому +1

    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 ?

  • @Willi_Zhang
    @Willi_Zhang Рік тому

    Thank you for this very helpful video!

  • @clausvind8010
    @clausvind8010 Рік тому

    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"

  • @samnangum2750
    @samnangum2750 Рік тому

    Thank for sharing Dr

  • @shashidharchavan3895
    @shashidharchavan3895 Рік тому

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

  • @dentoda
    @dentoda Рік тому

    Mlogit depvar indepvar, rrr gives OR output instead of coefficients

  • @bismarkanloadey289
    @bismarkanloadey289 2 роки тому

    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?

  • @kaushikjayaram8556
    @kaushikjayaram8556 Рік тому

    Thanks for sharing

  • @mdahsanul
    @mdahsanul Рік тому

    Thank you.

  • @jakobforslin6301
    @jakobforslin6301 2 роки тому

    Thank you very much!

  • @JiyongKim-et9sw
    @JiyongKim-et9sw 11 місяців тому

    Thanks !

  • @babaabba9348
    @babaabba9348 10 місяців тому

    Mycket bra!

  • @drisselghoufi6728
    @drisselghoufi6728 4 місяці тому

    Thank you🙏