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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Technical Report ; No. 2002,66
- Thema
-
Correlated binary data
Non-nested disposition model
Nested disposition model
Weibull distribution
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Odai, Reginald N. O.
Joachim, Kötting
Kwagyan, John
Bonney, George E.
Urfer, Wolfgang
- Ereignis
-
Veröffentlichung
- (wer)
-
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (wo)
-
Dortmund
- (wann)
-
2002
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Odai, Reginald N. O.
- Joachim, Kötting
- Kwagyan, John
- Bonney, George E.
- Urfer, Wolfgang
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Entstanden
- 2002
Ähnliche Objekte (12)
Correlated Weibull Regression Model for Multivariate Binary Data
Bootstrap based goodness-of-fit tests for binary multivariate regression models
Time series models for multivariate binary and categorical data
Multivariate spatial regression models
Applied multivariate data analysis, Vol. 1.. Regression and experimental design
Optimal designs for series estimation in nonparametric regression with correlated data
Multivariate and semiparametric kernel regression
Shape constraints in multivariate regression
Multivariate and Semiparametric Kernel Regression
Nonparametric Regression with Serially Correlated Errors
Response smoothing estimators in binary regression
Analyzing associations in multivariate binary time series
Correlated Weibull Regression Model for Multivariate Binary Data
Bootstrap based goodness-of-fit tests for binary multivariate regression models
Time series models for multivariate binary and categorical data
Multivariate spatial regression models
Applied multivariate data analysis, Vol. 1.. Regression and experimental design
Optimal designs for series estimation in nonparametric regression with correlated data
Multivariate and semiparametric kernel regression
Shape constraints in multivariate regression
Multivariate and Semiparametric Kernel Regression
Nonparametric Regression with Serially Correlated Errors
Response smoothing estimators in binary regression
Analyzing associations in multivariate binary time series
Correlated Weibull Regression Model for Multivariate Binary Data
Bootstrap based goodness-of-fit tests for binary multivariate regression models
Time series models for multivariate binary and categorical data
Multivariate spatial regression models
Applied multivariate data analysis, Vol. 1.. Regression and experimental design
Optimal designs for series estimation in nonparametric regression with correlated data
Multivariate and semiparametric kernel regression
Shape constraints in multivariate regression
Multivariate and Semiparametric Kernel Regression
Nonparametric Regression with Serially Correlated Errors
Response smoothing estimators in binary regression