Introduction to Ordinal Logistic Regression & Proportional Odds Assumption

Get Crystal clear understanding of Ordinal Logistic Regression.
To know step by step credit scoring, model design, multi collinearity treatment, variable selection, model validation etc, please refer to
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[@saugatadr]

After a long my coneption get cleared.Very nicely explained

[@LoizidesGeorge]

Gopal Thanks a lot this saved much time!! Regards Γ [next time you are in our mountainous region in Cyprus I "owe" you bbq :) , Let me know]

[@hemrajlamichhane8511]

Very nicely explained many thanks for the clarity

[@jaituteja88]

Great Video... Really appreciate your effort towards sharing the knowledge..!!

[@aimanhalim5430]

Nicely explained. Thank you so much. :-)

[@siddhantbhardwaj4268]

Amazing Explanation

[@sethulakshmig2999]

Sir, your class is excellent. You explained very clearly. May I ask you one doubt? How to do validation of the ordinal logistic regression model?

[@shubhamsinghania7699]

Thank you for the video sir, very well explained. I just want to come, if the Proportional Odds ratio is violated, can we use multinomial logisti9c regression keeping 0 as the base value as mentioned in the Agresti (2010) paper.

[@shawnabid7460]

Helpful, the logarithmic aspect could be more clear!

[@kossonouprunelle7576]

Thank you for your explanation. I have 2 nominal and 2 ordinal variables as independent variables (4), and 2 ordinal likert-scale dependent variable. In this case should i use ordinal logistic regression or nominal logistic regression? Your reply will help me a lot. Thank you in advance

[@gopalprasadmalakar12]

Kossonou, the decision is taken based on the type of dependent variable. In your case, dependent variable is ordinal so i will recommend to you ordinal regression. Regards

[@kossonouprunelle7576]

@@gopalprasadmalakar12 Thanks a lot