Hi All,
I'm running an Ordinal regression on a continuous independent variable and (obviously) an ordinal dependent variable. I'm doing the same for a number of continuous variables. So, I have many models. Some of these went well, but others either the assumption of proportional odds was not met and/or the model didn't fit the data well. I wonder, can I still use the p-value from these variables to say 'x' variable had or did not have an effect o the response variable?
All the best,
Laura
Dear Laura C. Salazar,
The following info below may be helpful:
How to interpret ordinal logistic regression results when independent variable is ordinal, too?
https://www.researchgate.net/post/How-to-interpret-ordinal-logistic-regression-results-when-independent-variable-is-ordinal-too
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Why does the "P" value of my independent variables change in my regression model whenever I add a new independent variable?
https://www.quora.com/Why-does-the-P-value-of-my-independent-variables-change-in-my-regression-model-whenever-I-add-a-new-independent-variable
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How should I interpret the p-values (i.e. t-tests) in regressions, and can I use them for feature selection?
https://stats.stackexchange.com/questions/47594/how-should-i-interpret-the-p-values-i-e-t-tests-in-regressions-and-can-i-use
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