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National Repository of Grey Literature 1 records found  Search took 0.01 seconds. 
Nonlinear Trend Modeling in the Analysis of Categorical Data
 Kalina, Jan
This paper studies various approaches to testing trend in the context of categorical data. While the linear trend is far more popular in econometric applications, a nonlinear modeling of the trend allows a more subtle information extraction from real data, especially if the linearity of the trend cannot be expected and verified by hypothesis testing. We exploit the exact unconditional approach to propose alternative versions of some trend tests. One of them is the test of relaxed trend (Liu, 1998), who proposed a generalization of the classical Cochran- Armitage test of linear trend. A numerical example on real data reveals the advantages of the test of relaxed trend compared to the classical test of linear trend. Further, we propose an exact unconditional test also for modeling association between an ordinal response and nominal regressor. Further, we propose a robust estimator of parameters in the logistic regression model, which is based on implicit weighting of individual observations. We assess the breakdown point of the newly proposed robust estimator.
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