Estimation Of Duration And Competing Risks Models In Presence Of Attrition PDF Download
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Author | : Kenneth Carling |
Publisher | : |
Total Pages | : 16 |
Release | : 1994 |
Genre | : |
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Download Estimation of Duration and Competing Risks Models in Presence of Attrition Book in PDF, ePub and Kindle
Author | : David Troncoso-Ponce |
Publisher | : |
Total Pages | : 23 |
Release | : 2018 |
Genre | : |
ISBN | : |
Download Estimation of Competing Risks Duration Models with Unobserved Heterogeneity Using Hsmlogit Book in PDF, ePub and Kindle
This article presents hsmlogit, a new Stata command that estimates multispells discrete time competing risks duration models with unobserved heterogeneity. hsmlogit allows for the estimation of one, two and up to three competing risks, as well as a maximum of ve points of support for the identication of unobserved heterogeneity distribution (Heckman and Singer, 1984). The main contribution of hsmlogit is that allows for exploiting the richness of large longitudinal micro datasets, by estimating competing risks duration models, instead of one-risk models (such as hshaz and hshaz2), as well as it takes into account the presence of unobserved heterogeneity affecting transition rates. In addition to this, and taking into account the larger size of longitudinal micro datasets used for the estimation of discrete time duration models, hsmlogit also provides the algebraic expressions of both rst and second order derivatives that, respectively, dene the gradient vector and Hessian matrix, which signicantly reduce time required to achieve model convergence.
Author | : David Troncoso Ponce |
Publisher | : |
Total Pages | : 23 |
Release | : 2018 |
Genre | : |
ISBN | : |
Download Estimation of Competing Risks Duration Model with Unobserved Heterogeneity Using Hsmlogit Book in PDF, ePub and Kindle
Author | : Aaron K. Han |
Publisher | : |
Total Pages | : 60 |
Release | : 1986 |
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Download Semiparametric Estimation of Duration and Competing Risk Models Book in PDF, ePub and Kindle
Author | : Uppsala universitet. Statistiska institutionen |
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Total Pages | : 24 |
Release | : 1994 |
Genre | : Statistics |
ISBN | : |
Download Research Report - University of Uppsala, Department of Statistics Book in PDF, ePub and Kindle
Author | : Glen T. Sueyoshi |
Publisher | : |
Total Pages | : 48 |
Release | : 1990 |
Genre | : Competing risks |
ISBN | : |
Download Semi-parametric Proportional Hazards Estimation of Competing Risks Models with Time-varying Covariates Book in PDF, ePub and Kindle
Author | : |
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Total Pages | : |
Release | : 2020 |
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Download Marginal Survival Estimation In the Presence of Competing Risks for Copula Models Book in PDF, ePub and Kindle
Author | : Brian Stephen Rickard |
Publisher | : |
Total Pages | : 226 |
Release | : 2015 |
Genre | : Competing risks |
ISBN | : 9781321708790 |
Download Analytical Comparison of Contrasting Approaches to Estimating Competing Risks Models Book in PDF, ePub and Kindle
Survival analysis is a commonly used tool in many fields but has seen little use in education research despite a common number of research questions for which it is well suited. Researchers often use logistic regression instead; however, this omits useful information. In research on retention and graduation for example, the timing of the event is an important piece of information omitted when using logistic regression. A simulation study was conducted to evaluate four methods of analyzing competing risks survival data, Cox proportional hazards regression, Weibull regression, Fine and Gray's Method, and Cox proportional hazards regression with frailty. College student retention and graduation is presented as an example. The results indicate that there is no one best model for all simulated scenarios. Instead, it appears the selection of the method of analysis should be based on the characteristics of the data. Both Cox proportional hazards and the Weibull regression are accurate with the base combination (sample size of 500 per group, continuous event time format, no correlation between event times, homogeneous shape parameter for both events for both groups, homogeneous failure rates for both events for both groups, and no frailty) as well as when one parameter is changed from the base combination. In addition, for data where the event time distribution shape does not differ by event, the accuracy of the models is quite similar. However, differences begin to emerge with some combinations of conditions. Cox performs especially poorly with data sets containing both differing event time distribution shapes by event and differing failure rates by group or event while Weibull is least accurate with the combination of homogeneous event time distribution shape, heterogeneous failure rate by group and/or event, and discrete format time. Fine and Gray's method was often ranked last by accuracy, but there are some situations where its accuracy is quite good including retention and graduation data. Cox proportional hazards regression with frailty performed very similarly to the Cox regression without frailty with no clear benefits.
Author | : Yushun Lin |
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Total Pages | : |
Release | : 2011 |
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Download Parametric Estimation in Competing Risks and Multi-state Models Book in PDF, ePub and Kindle
Author | : |
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Total Pages | : |
Release | : 1996 |
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Download Flexible Parametric Estimation of Duration and Competing Risk Models Book in PDF, ePub and Kindle
Cf.: http://dx.doi.org/10.3886/ICPSR01024.v1.