Multinominal logistic regression, Part 1: Introduction

This video introduces the method and when it should be used. It shows a simple example with one explanatory variable to illustrate how the method works and how the results can be interpreted using either odds ratios or predicted probabilities.
This video is part of NCRM Online Resource on Multinominal logistic regression by Dr Dr Heini Väisänen. To view the resource (which includes, slides, worksheet, data and reading list) visit www.ncrm.ac.uk/resources/online/
Please note: we may be unable to respond to individual questions on this video.
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Пікірлер: 22

  • @tatianabarcenasbarreto6967
    @tatianabarcenasbarreto6967 Жыл бұрын

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

  • @f.181
    @f.1812 жыл бұрын

    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

    @asadyare3268

    6 ай бұрын

    You are right.

  • @Sanjeevpudasaini
    @Sanjeevpudasaini2 жыл бұрын

    Thank you so much for such a good explanation!

  • @Robin-zc2iw
    @Robin-zc2iw Жыл бұрын

    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

    9 ай бұрын

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

  • @Willi_Zhang
    @Willi_Zhang11 ай бұрын

    Thank you for this very helpful video!

  • @KayYesYouTuber
    @KayYesYouTuber8 ай бұрын

    Good explanation of multinomial logistic regression.

  • @samnangum2750
    @samnangum2750 Жыл бұрын

    Thank for sharing Dr

  • @drisselghoufi6728
    @drisselghoufi672814 күн бұрын

    Thank you🙏

  • @jakobforslin6301
    @jakobforslin63012 жыл бұрын

    Thank you very much!

  • @bismarkanloadey289
    @bismarkanloadey2892 жыл бұрын

    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 Жыл бұрын

    Thanks for sharing

  • @JiyongKim-et9sw
    @JiyongKim-et9sw7 ай бұрын

    Thanks !

  • @prempant6428
    @prempant6428 Жыл бұрын

    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
    @KyambaddeFrancis-ih8uk2 ай бұрын

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

  • @clausvind8010
    @clausvind8010 Жыл бұрын

    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

    @clausvind8010

    Жыл бұрын

    slide not sliste

  • @shashidharchavan3895
    @shashidharchavan3895 Жыл бұрын

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

  • @dentoda
    @dentoda8 ай бұрын

    Mlogit depvar indepvar, rrr gives OR output instead of coefficients

  • @babaabba9348
    @babaabba93486 ай бұрын

    Mycket bra!

  • @littlenuts779
    @littlenuts7794 ай бұрын

    Why the numerator of pi3 is 1 as the reference category?

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