Modeling multicategorical outcomes in SPSS 29 using multinomial logistic regression (Sept 2023, rev)

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  • Опубликовано: 17 сен 2023
  • This video demonstrates how to perform a basic multinomial logistic regression using SPSS version 29.
    A copy of the SPSS data file can be downloaded here:
    drive.google.com/file/d/1QolB...
    A copy of the Powerpoint file referenced in the video can be downloaded here:
    drive.google.com/file/d/1DOsZ...
    A copy of a Word document with an example write-up can be downloaded here:
    drive.google.com/file/d/1LCKR...

Комментарии • 8

  • @user-xn4qr8qq6f
    @user-xn4qr8qq6f Месяц назад

    Thank you so much

  • @turkmura81
    @turkmura81 10 месяцев назад

    Another great video! Thanks Dr. Crowson!❤

  • @kyawtunnaing9225
    @kyawtunnaing9225 9 месяцев назад

    Thanks for your video lecture.

  • @HauNguyen-rw3mi
    @HauNguyen-rw3mi 7 месяцев назад

    Thank you sooooo soooooo much

  • @dsavkay
    @dsavkay 4 месяца назад

    Great!!!

  • @yaxyemaxamed7878
    @yaxyemaxamed7878 5 месяцев назад

    Thank u lecturer

  • @m1stylark
    @m1stylark Месяц назад

    Hi Mike. I really, really need your help and advice. May i share my spss problem with you? i have this warning message : "Unexpected singularities in the Hessian matrix are encountered. This indicates that either some predictor variables should be excluded or some categories should be merged.
    The NOMREG procedure continues despite the above warning(s). Subsequent results shown are based on the last iteration. Validity of the model fit is uncertain'.
    I am not sure how to troubleshoot this. I am a newbie. Google, youtube, researchgate and reddit could not help me =( Could you kindly guide me?

  • @mrister24
    @mrister24 9 месяцев назад

    Great video. I've been running one of these and trying to figure out why my Goodness-of-Fit box is all zeroed out. I just have a factor with 3 levels and a dependent variable with 4 levels so I'm not sure why I'm not getting this output, though the model is predicting 100% of my cases to belong to the first (reference) group so maybe it's just a poor model...?