An Ordinal Regression Model using Dealer Satisfaction Data
This article analyses dealer satisfaction data in the agricultural technology market in Germany. The dealers could rate their suppliers in the 'overall satisfaction' and in 38 questions which can be summarized in 8 dimensions. An ordinal regression model which is also known as the proportional odds model is used to analyse the ordinal scaled rating of the dealers. The ordinal regression model is a well examined method in econometric theory, but many authors prefer using a linear regression model due to better interpretation, even the assumptions of a linear regression do not fit the data. Since the estimated coefficients of an ordinal regression model can not be properly interpreted we show other methods for a better insight of the relationship of the dealer satisfaction and the influencing variables. These methods are easy to use and it is recommended to list some of them in empirical papers.
|Date of creation:||May 2007|
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- Philip Hans Franses & J.S. Cramer, 2010.
"On the number of categories in an ordered regression model,"
Netherlands Society for Statistics and Operations Research, vol. 64(1), pages 125-128.
- Franses, Ph.H.B.F. & Cramer, J.S., 2002. "On the number of categories in an ordered regression model," Econometric Institute Research Papers EI 2002-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Rory Wolfe & William Gould, 1998. "An approximate likelihood-ratio test for ordinal response models," Stata Technical Bulletin, StataCorp LP, vol. 7(42). Full references (including those not matched with items on IDEAS)
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