Arbeitspapier
Correlated Weibull regression model for multivariate binary data
The correlated Weibull regression model for the analysis of correlated binary data is presented. This regression model is based on Bonney’s disposition model for the regression analysis of correlated binary outcomes. Parameter estimation was done through the maximum likelihood method. The correlated Weibull regression model was contrasted with the correlated logistic regression model. The results showed that both regression models were useful in explaining the familial aggregation of oesophageal cancer. The correlated logistic regression model fitted the oesophageal cancer data better than the correlated Weibull regression model for both the non-nested and nested cases. Furthermore, the correlated logistic regression model was computationally more attractive than the correlated Weibull regression model.
- Language
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Englisch
- Bibliographic citation
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Series: Technical Report ; No. 2002,66
- Subject
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Correlated binary data
Non-nested disposition model
Nested disposition model
Weibull distribution
- Event
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Geistige Schöpfung
- (who)
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Odai, Reginald N. O.
Joachim, Kötting
Kwagyan, John
Bonney, George E.
Urfer, Wolfgang
- Event
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Veröffentlichung
- (who)
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Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
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Dortmund
- (when)
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2002
- Handle
- Last update
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10.03.2025, 11:41 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Odai, Reginald N. O.
- Joachim, Kötting
- Kwagyan, John
- Bonney, George E.
- Urfer, Wolfgang
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2002
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Multivariate spatial regression models
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Multivariate and semiparametric kernel regression
Shape constraints in multivariate regression
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Response smoothing estimators in binary regression