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Cutoff sample size estimation for survival data: a simulation studyChe, Huiwen January 2014 (has links)
This thesis demonstrates the possible cutoff sample size point that balances goodness of es-timation and study expenditure by a practical cancer case. As it is crucial to determine the sample size in designing an experiment, researchers attempt to find the suitable sample size that achieves desired power and budget efficiency at the same time. The thesis shows how simulation can be used for sample size and precision calculations with survival data. The pre-sentation concentrates on the simulation involved in carrying out the estimates and precision calculations. The Kaplan-Meier estimator and the Cox regression coefficient are chosen as point estimators, and the precision measurements focus on the mean square error and the stan-dard error.
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Hedge Funds and Survival AnalysisNhogue Wabo, Blanche Nadege 24 October 2013 (has links)
Using data from Hedge Fund Research, Inc. (HFR), this study adapts and expands
on existing methods in survival analysis in an attempt to investigate whether hedge
funds mortality can be predicted on the basis of certain hedge funds characteristics.
The main idea is to determine the characteristics which contribute the most to the
survival and failure probabilities of hedge funds and interpret them. We establish hazard
models with time-independent covariates, as well as time-varying covariates to interpret
the selected hedge funds characteristics. Our results show that size, age, performance,
strategy, annual audit, fund offshore and fund denomination are the characteristics that
best explain hedge fund failure. We find that 1% increase in performance decreases
the hazard by 3.3%, the small size and the less than 5 years old hedge funds are the
most likely to die and the event-driven strategy is the best to use as compare to others.
The risk of death is 0.668 times lower for funds who indicated that an annual audit
is performed as compared to the funds who did not indicated that an annual audit is
performed. The risk of death for the offshore hedge funds is 1.059 times higher than the
non-offshore hedge funds.
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Dependency estimation over a finite bivariate failure time region /Fan, Juanjuan, January 1997 (has links)
Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (leaves [100]-103).
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Fitting of survival functions for grouped data on insurance policiesLouw, Elizabeth Magrietha. January 2005 (has links)
Thesis (PhD)(Actuarial Science) -- University of Pretoria, 2002. / Includes bibliographical references.
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The general linear model for censored dataZhao, Yonggang, January 1900 (has links)
Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xiv, 113 p.; also includes graphics Includes bibliographical references (p. 108-113). Available online via OhioLINK's ETD Center
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Proportional odds model for survival data /Leung, Tsui-lin. January 1999 (has links)
Thesis (M. Phil.)--University of Hong Kong, 1999. / Includes bibliographical references (leaves 85-88).
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Sequential analysis of clustered survival data by marginal methodsHou, Bo, January 2008 (has links)
Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Statistics and Biostatistics." Includes bibliographical references (p. 50-52).
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Proportional odds model for survival dataLeung, Tsui-lin. January 1999 (has links)
Thesis (M.Phil.)--University of Hong Kong, 1999. / Includes bibliographical references (leaves 85-88) Also available in print.
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Extensions on long-term survivor model with random effects /Lai, Xin. January 2009 (has links) (PDF)
Thesis (Ph.D.)--City University of Hong Kong, 2009. / "Submitted to Department of Management Sciences in partial fulfillment of the requirement for the degree of Doctor of Philosophy." Includes bibliographical references (leaves 118-126)
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Hedge Funds and Survival AnalysisNhogue Wabo, Blanche Nadege January 2013 (has links)
Using data from Hedge Fund Research, Inc. (HFR), this study adapts and expands
on existing methods in survival analysis in an attempt to investigate whether hedge
funds mortality can be predicted on the basis of certain hedge funds characteristics.
The main idea is to determine the characteristics which contribute the most to the
survival and failure probabilities of hedge funds and interpret them. We establish hazard
models with time-independent covariates, as well as time-varying covariates to interpret
the selected hedge funds characteristics. Our results show that size, age, performance,
strategy, annual audit, fund offshore and fund denomination are the characteristics that
best explain hedge fund failure. We find that 1% increase in performance decreases
the hazard by 3.3%, the small size and the less than 5 years old hedge funds are the
most likely to die and the event-driven strategy is the best to use as compare to others.
The risk of death is 0.668 times lower for funds who indicated that an annual audit
is performed as compared to the funds who did not indicated that an annual audit is
performed. The risk of death for the offshore hedge funds is 1.059 times higher than the
non-offshore hedge funds.
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