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Title:Application of the disposition model to breast cancer data PDF Logo
Authors:Odai, Reginald N. O.
Urfer, Wolfgang
Kötting, Joachim
Bonney, George E.
Issue Date:2003
Series/Report no.:Technical Report // Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2003,14
Abstract:In this paper, we have presented the second level nesting of Bonney's disposition model (Bonney, 1998) and examined the implications of higher level nesting of the disposition model in relation to the dimension of the parameter space. We have also compared the performance of the disposition model with Cox's regression model (Cox, 1972). It has been observed that the disposition model has a very large number of unknown parameters, and is therefore limited by the method of estimation used. In the case of the maximum likelihood method, reasonable estimates are obtained if the number of parameters in the model is at most nine. This corresponds to about four to seven covariates. Since each covariate in Cox's model provides a parameter, it is possible to include more covariates in the regression analysis. On the other hand, as opposed to Cox's model, the disposition model is fitted with parameters to capture aggregation in families, if there should be any. The choice of a particular model should therefore depend on the available data set and the purpose of the statistical analysis.
Subjects:Second level nesting
Proportional hazards model
Quadratic exponential form
Partial likelihood
Familial aggregation
Second-order methods
Marginal models
Conditional models
Document Type:Working Paper
Appears in Collections:Technical Reports, SFB 475: Komplexitätsreduktion in multivariaten Datenstrukturen, TU Dortmund

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