The method of analysis for my research is ordinal regression contains 6 ranked variables. But the goodness of shows unexpected and i am confused.
Is this really possible, my data fit well or not?
or There must errors ? {If so, what type of errors are commonly faced while using ordinal regression}
Hello Anil,
The fit indices you obtained suggest that the multinomial model derived from your data performs well to account for the observed values on your DV. Significant values would imply a mis-specified model (in some way).
Here's a link to a simple explanation that you may find helpful: https://support.minitab.com/en-us/minitab/18/help-and-how-to/modeling-statistics/regression/how-to/ordinal-logistic-regression/interpret-the-results/all-statistics/goodness-of-fit-tests/
Good luck with your work.
Hello Anil,
The fit indices you obtained suggest that the multinomial model derived from your data performs well to account for the observed values on your DV. Significant values would imply a mis-specified model (in some way).
Here's a link to a simple explanation that you may find helpful: https://support.minitab.com/en-us/minitab/18/help-and-how-to/modeling-statistics/regression/how-to/ordinal-logistic-regression/interpret-the-results/all-statistics/goodness-of-fit-tests/
Good luck with your work.
Please look at the assumptions especially multicolinearity and proportional odds and interpret them. Interpret and report the overall goodness of fit and the likelihood-ratio test. I use SPSS for these kinds of analyses so, I will refer you to it. Follow the link attached, please. https://statistics.laerd.com/spss-tutorials/ordinal-regression-using-spss-statistics-3.php
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