Ordinal regression Part 1: Introduction

This video introduced the method and its cumulative nature. It shows a simple example with one explanatory variable to illustrate how the method works and how the results can be interpreted using either cumulative odds or predicted probabilities.
This video is part of an Online Resource created by NCRM. To access the full resource (which includes, worksheet, data, slides and reading list) please visit www.ncrm.ac.uk/resources/online/
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[@llshadygal6451]

Great series, This was super helpful!! Look forward to more videos!!

[@nathansteffens5033]

Fantastic video. The best on ordinal regression that I've seen. Thank you.

[@dillik.c.9955]

Excellent lecture on ordinal regression model. I had never watch such lecture before, very simple and precise. Worth watching

[@teresamota5800]

These series helped me so much with my dissertation. Thank you a lot

[@yesodabhargava8776]

Great lecture. Thank you so much.

[@Jack-zd5ls]

Brilliant explanation!

[@BBkhadka]

Thank you so mcuh for insightful lecture series.

[@landersebastian7886]

Thank you

[@manuelleitner3196]

Hello and thank you for this GREAT video and explanation. I just have one question: what if my ordinal response variable (Y) has more than 3 categories, for example 7. Is the interpretation of the OR the same; like: "For students with educated parents (par =1), the odds of very likely versus all combined other six categories are exp(1.127) = 3.09 greater compared to students with non-educated parents (par=0)"? Or how would the interpretation be? Thank you very much in advance!

[@manuelleitner3196]

aah ok the 2nd part of your video series gives more insight into that problem !!:)

[@tamanudghosh4560]

Dear Dr. Heini, Could you please share your email id? I need your expert guidance on the sample size calculation for an ordered logistic regression model in the context of my study.