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4. Modelling Survival Data in Medical Research

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This article is published in Journal of The Royal Statistical Society Series A-statistics in Society.The article was published on 1995-01-01. It has received 1092 citations till now. The article focuses on the topics: Medical research.

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Citations
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The Poisson-exponential model for recurrent event data: an application to bowel motility data

TL;DR: In this paper, the authors presented a new parametric model for recurrent events, in which the time of each recurrence is associated to one or multiple latent causes and no information is provided about the responsible cause for the event.
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Reliability study of proportional odds family of discrete distributions

TL;DR: In this article, the authors considered the Marshall-Olkin family of distributions in discrete case with fixed tilt parameter and studied different ageing properties, as well as different stochastic orderings of the distributions.

Jádrové odhady rizikové funkce

TL;DR: In this article disertacni prace se věnuje metodam pro zpracovani cenzorovaných dat v analýze přežiti.
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Development and performance of npde for the evaluation of time-to-event models

TL;DR: It is shown that npde can be readily extended to time-to-event (TTE) models and that they perform well with an adequate type I error and power to detect model misspecifications for TTE data.
References
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Journal ArticleDOI

Mineral Metabolism, Mortality, and Morbidity in Maintenance Hemodialysis

TL;DR: Hyperphosphatemia and hyperparathyroidism were significantly associated with all-cause, cardiovascular, and fracture-related hospitalization, and the population attributable risk percentage for disorders of mineral metabolism was 17.5%, owing largely to the high prevalence of hyperph phosphatemia.
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Overall Survival and Updated Results for Sunitinib Compared With Interferon Alfa in Patients With Metastatic Renal Cell Carcinoma

TL;DR: Sunitinib demonstrates longer overall survival compared with IFN-alpha plus improvement in response and progression-free survival in the first-line treatment of patients with metastatic RCC, highlighting an improved prognosis in patients with RCC in the era of targeted therapy.
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Survival and Prognostic Stratification of 670 Patients With Advanced Renal Cell Carcinoma

TL;DR: Five prognostic factors for predicting survival were identified and used to categorize patients with metastatic RCC into three risk groups, for which the median survival times were separated by 6 months or more.