Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score
In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score...
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| Autor*in: |
Van Oirbeek, Robin [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Rechteinformationen: |
Nutzungsrecht: Copyright © Taylor & Francis Group, LLC 2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Communications in statistics / Simulation and computation - New York, NY : Dekker, 1982, 45(2016), 9, Seite 3294-3306 |
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| Übergeordnetes Werk: |
volume:45 ; year:2016 ; number:9 ; pages:3294-3306 |
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| DOI / URN: |
10.1080/03610918.2014.936464 |
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| 520 | |a In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. | ||
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10.1080/03610918.2014.936464 doi PQ20161012 (DE-627)OLC1982455217 (DE-599)GBVOLC1982455217 (PRQ)c1525-876dc978e390d619c080de8155faaf5304618c43b3b2252404a3d89094cc8df70 (KEY)0108850520160000045000903294exploringtheclusteringeffectofthefrailtysurvivalmo DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Van Oirbeek, Robin verfasserin aut Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC 2016 Predictive ability Frailty model Clustering 62N99 Survival analysis Brier score Frailty Confidence intervals Lesaffre, Emmanuel oth Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 45(2016), 9, Seite 3294-3306 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:45 year:2016 number:9 pages:3294-3306 http://dx.doi.org/10.1080/03610918.2014.936464 Volltext http://www.tandfonline.com/doi/abs/10.1080/03610918.2014.936464 http://search.proquest.com/docview/1808754413 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 45 2016 9 3294-3306 |
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10.1080/03610918.2014.936464 doi PQ20161012 (DE-627)OLC1982455217 (DE-599)GBVOLC1982455217 (PRQ)c1525-876dc978e390d619c080de8155faaf5304618c43b3b2252404a3d89094cc8df70 (KEY)0108850520160000045000903294exploringtheclusteringeffectofthefrailtysurvivalmo DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Van Oirbeek, Robin verfasserin aut Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC 2016 Predictive ability Frailty model Clustering 62N99 Survival analysis Brier score Frailty Confidence intervals Lesaffre, Emmanuel oth Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 45(2016), 9, Seite 3294-3306 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:45 year:2016 number:9 pages:3294-3306 http://dx.doi.org/10.1080/03610918.2014.936464 Volltext http://www.tandfonline.com/doi/abs/10.1080/03610918.2014.936464 http://search.proquest.com/docview/1808754413 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 45 2016 9 3294-3306 |
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10.1080/03610918.2014.936464 doi PQ20161012 (DE-627)OLC1982455217 (DE-599)GBVOLC1982455217 (PRQ)c1525-876dc978e390d619c080de8155faaf5304618c43b3b2252404a3d89094cc8df70 (KEY)0108850520160000045000903294exploringtheclusteringeffectofthefrailtysurvivalmo DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Van Oirbeek, Robin verfasserin aut Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC 2016 Predictive ability Frailty model Clustering 62N99 Survival analysis Brier score Frailty Confidence intervals Lesaffre, Emmanuel oth Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 45(2016), 9, Seite 3294-3306 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:45 year:2016 number:9 pages:3294-3306 http://dx.doi.org/10.1080/03610918.2014.936464 Volltext http://www.tandfonline.com/doi/abs/10.1080/03610918.2014.936464 http://search.proquest.com/docview/1808754413 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 45 2016 9 3294-3306 |
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10.1080/03610918.2014.936464 doi PQ20161012 (DE-627)OLC1982455217 (DE-599)GBVOLC1982455217 (PRQ)c1525-876dc978e390d619c080de8155faaf5304618c43b3b2252404a3d89094cc8df70 (KEY)0108850520160000045000903294exploringtheclusteringeffectofthefrailtysurvivalmo DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Van Oirbeek, Robin verfasserin aut Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC 2016 Predictive ability Frailty model Clustering 62N99 Survival analysis Brier score Frailty Confidence intervals Lesaffre, Emmanuel oth Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 45(2016), 9, Seite 3294-3306 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:45 year:2016 number:9 pages:3294-3306 http://dx.doi.org/10.1080/03610918.2014.936464 Volltext http://www.tandfonline.com/doi/abs/10.1080/03610918.2014.936464 http://search.proquest.com/docview/1808754413 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 45 2016 9 3294-3306 |
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exploring the clustering effect of the frailty survival model by means of the brier score |
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Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score |
| abstract |
In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. |
| abstractGer |
In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. |
| abstract_unstemmed |
In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a "conditional Brier score" and a "marginal Brier score." Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset. |
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Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score |
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Lesaffre, Emmanuel |
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