Goodness-of-fit tests for ordinal response regression models

2004 ◽  
Vol 23 (6) ◽  
pp. 999-1014 ◽  
Author(s):  
Erik Pulkstenis ◽  
Timothy J. Robinson
Keyword(s):  
Regression Models ◽  
Goodness Of Fit ◽  
Ordinal Response ◽  
Goodness Of Fit Tests

Goodness-of-Fit Tests for Ordinal Response Regression Models

1996 ◽  
Vol 45 (2) ◽  
pp. 175 ◽  
Author(s):  
Stuart R. Lipsitz ◽  
Garrett M. Fitzmaurice ◽  
Geert Molenberghs
Keyword(s):  
Regression Models ◽  
Goodness Of Fit ◽  
Ordinal Response ◽  
Goodness Of Fit Tests

Model-based goodness-of-fit tests for the ordered stereotype model

2019 ◽  
Vol 29 (6) ◽  
pp. 1527-1541
Author(s):  
Daniel Fernández ◽  
Ivy Liu ◽  
Richard Arnold ◽  
Thuong Nguyen ◽  
Martin Spiess
Keyword(s):  
Alternative Model ◽  
Binary Data ◽  
Goodness Of Fit ◽  
Null Model ◽  
Response Variable ◽  
Model Based ◽  
Ordinal Response ◽  
Goodness Of Fit Tests ◽  
Lemeshow Test ◽  
Group Effects

This paper presents two new model-based goodness-of-fit tests for the ordered stereotype model applied to an ordinal response variable. The proposed tests are based on the Lipsitz test, which partitions the subjects into G groups following the popular Hosmer–Lemeshow test for binary data. The tests construct an alternative model where group effects are added into the null model. If the model fits the data well then the null model is correct, and there should be no group effects. One of the main advantages of the ordered stereotype model is that it allows us to determine a new uneven spacing of the ordinal response categories, dictated by the data. The two proposed tests use this new adjusted spacing. One test uses the form of the original ordered stereotype model, and the other uses an ordinary linear model. We demonstrate the performance of both tests under a variety of scenarios. Finally, the results of the application in three examples are presented.

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