Survival data are often clustered into groups, such as couples, families, communities, and geographical regions. Observations from same cluster usually share certain unobserved characteristics and as a result tend to be correlated. In multivariate proportional hazards model correlations among observations are considered. In analysis if associations among observations are ignored, standard error of the estimates of parameters of interest may be incorrect. The parameters estimates yielded by the multivariate proportional hazards model are very similar to those yielded by the standard hazards model. Present research deals with the extension of the Cox model that allows for heterogeneity due to omitted covariates using frailty (random effect) approach, and there by uses a more general class of mixed-modeling that estimates predictors via parametric and non-parametric regression. In this study, Cox model and multivariate proportional hazards model are used for analyzing birth interval of Bangladesh using Bangladesh Demographic and Health Survey (BDHS, 2004) data. This result of this study indicates that, the unobserved cluster effect has a sizeable impact on birth interval in Bangladesh.
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LecturerInstitute of Statistical Research and TrainingUniversity of DhakaDhaka-1000
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Survival data are often clustered into groups, such as couples, families, communities, and geographical regions. Observations from same cluster usually share certain unobserved characteristics and as a result tend to be correlated. In multivariate proportional hazards model correlations among observations are considered. In analysis if associations among observations are ignored, standard error of the estimates of parameters of interest may be incorrect. The parameters estimates yielded by the multivariate proportional hazards model are very similar to those yielded by the standard hazards model. Present research deals with the extension of the Cox model that allows for heterogeneity due to omitted covariates using frailty (random effect) approach, and there by uses a more general class of mixed-modeling that estimates predictors via parametric and non-parametric regression. In this study, Cox model and multivariate proportional hazards model are used for analyzing birth interval of Bangladesh using Bangladesh Demographic and Health Survey (BDHS, 2004) data. This result of this study indicates that, the unobserved cluster effect has a sizeable impact on birth interval in Bangladesh. 148 pp. Englisch. Bestandsnummer des Verkäufers 9783848442492
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mahmood SharifLecturerInstitute of Statistical Research and TrainingUniversity of DhakaDhaka-1000Survival data are often clustered into groups, such as couples, families, communities, and geographical regions. Observations from . Bestandsnummer des Verkäufers 5522507
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Survival data are often clustered into groups, such as couples, families, communities, and geographical regions. Observations from same cluster usually share certain unobserved characteristics and as a result tend to be correlated. In multivariate proportional hazards model correlations among observations are considered. In analysis if associations among observations are ignored, standard error of the estimates of parameters of interest may be incorrect. The parameters estimates yielded by the multivariate proportional hazards model are very similar to those yielded by the standard hazards model. Present research deals with the extension of the Cox model that allows for heterogeneity due to omitted covariates using frailty (random effect) approach, and there by uses a more general class of mixed-modeling that estimates predictors via parametric and non-parametric regression. In this study, Cox model and multivariate proportional hazards model are used for analyzing birth interval of Bangladesh using Bangladesh Demographic and Health Survey (BDHS, 2004) data. This result of this study indicates that, the unobserved cluster effect has a sizeable impact on birth interval in Bangladesh. Bestandsnummer des Verkäufers 9783848442492
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Survival data are often clustered into groups, such as couples, families, communities, and geographical regions. Observations from same cluster usually share certain unobserved characteristics and as a result tend to be correlated. In multivariate proportional hazards model correlations among observations are considered. In analysis if associations among observations are ignored, standard error of the estimates of parameters of interest may be incorrect. The parameters estimates yielded by the multivariate proportional hazards model are very similar to those yielded by the standard hazards model. Present research deals with the extension of the Cox model that allows for heterogeneity due to omitted covariates using frailty (random effect) approach, and there by uses a more general class of mixed-modeling that estimates predictors via parametric and non-parametric regression. In this study, Cox model and multivariate proportional hazards model are used for analyzing birth interval of Bangladesh using Bangladesh Demographic and Health Survey (BDHS, 2004) data. This result of this study indicates that, the unobserved cluster effect has a sizeable impact on birth interval in Bangladesh.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 148 pp. Englisch. Bestandsnummer des Verkäufers 9783848442492
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Taschenbuch. Zustand: Neu. Multivariate Proportional Hazards Model | an Application to the Birth Interval in Bangladesh | Sharif Mahmood (u. a.) | Taschenbuch | 148 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783848442492 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 106469952
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