Survival data
Bayesian analysis and model selection for interval censored survival data
... BAYESIAN ANALYSIS AND MODEL SELECTION FOR INTERVAL-CENSORED SURVIVAL DATA!. by.[r] ...
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Robust Learning for Optimal Treatment Strategy with Survival Data
... censored data with flexible number of decision ...optimal survival time when the optimal Q- function belongs to the approximation ...censored data, which provided doubly robust and consistent ...
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Transformation Models for Survival Data Analysis with Applications
... relapse-free survival time, it can be used to overall survival time as ...the survival time of a patient and several risk factors based on two cohorts data from the First National Health and ...
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Survival data management in patients with acute myocardial infarction
... ABSTRACT: The aim of this study is to analyse survival data of the patients with acute myocardial infarction. We studied a sample of 424 patients with a mean age of 67.1±12.3 years. The overall mortality ...
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Individual patient data meta-analysis of survival data using Poisson regression models
... count data and contingency tables; however, the extension to model- ling survival data via a piecewise exponential model [19] serves as an alternative approach to the widely used Cox ...
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An Application of Generalized Entropy Optimization Methods in Survival Data Analysis
... paper, survival data analysis is realized by applying Generalized En- tropy Optimization Methods ...statistical data. For this reason, survival data analysis by GEOD acquires a new ...
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Some Importance Models inspect to Survival Data Inference
... This paper used some models inspect to survival data analysis and focused on the Cox regression model characteristics. This paper also used liver cancer data from Khartoum State Health Ministry ...
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Bayesian semiparametric methods for longitudinal, multivariate, and survival data
... for data collected from tumorigenicity studies, including ease of computation via MCMC, ability to incorporate prior infor- mation ...time data in ...multivariate survival data, refer to pa- ...
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Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves
... Meier data nor the reconstruction of life-table data, but was a necessary step that had to be taken in order for the authors to illustrate methods for combining survival data from sev- eral ...
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Strategies for power calculations in predictive biomarker studies in survival data
... fixed survival time and censored status (i.e., survival data have been ...preliminary data for discovering the biomarker has an overall MST of 6 years, but the study cohort you plan to ...
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Anatomic distribution, clinical features, and survival data of 87 cases primary gastrointestinal lymphoma
... The surgical treatment was traditionally considered as the main treatment methods of PGIL. Most of pa- tients accepted the radical resection. Palliative resec- tion might due to huge size of tumor or extensive transfer ...
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Network meta-analysis of survival data with fractional polynomials
... the survival function has a great impact on the expected survival this assumption may lead to biased or at least highly uncertain estimates regarding differences in expected survival and therefore ...
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Malignant Pediatric Gliosarcoma Defies General Survival Data
... Pediatric gliosarcoma is evidently rare, and survival dictated by the disease is poor even with the best of multimodality approaches. This case of an 11 years old boy in his preadoles- cence treated with near ...
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Behrens-Fisher Analogs for Discrete and Survival Data
... the survival time or time to a certain event like time to death, time it takes for a patient to respond to a therapy, time from response until disease relapse ...time data is well known (Lawless (1982); ...
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Change Point Analysis of Survival Data with Application in Clinical Trials
... The goal of this paper is to find efficient change-point detection methods for the piecewise constant failure rate models [5] [6] [8] [15] with unknown pre-change and post-change parameters. Maximum likelihood estima- ...
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"Smooth" Inference for Clustered Survival Data
... Louis (2000) and Pan and Connett (2001) for right-censored data. They proposed an EM-like algorithm, where censored survival time are imputed through a Buckley- James type approach. But they required that ...
164
On Hybrid Censored Inverse Lomax Distribution: Application to the Survival Data
... In this section, we considered Bayes procedure to obtain the point and interval estimates of the parameters α, β in presence of hybrid censored data. The Bayes estimators are derived under Jeffrey’s non-informative ...
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Statistical Methods For Truncated Survival Data
... time-to-event data. For example, autopsy-confirmed survival studies of neurodegenerative diseases are subject to selection bias due to the simultaneous presence of left and right truncation, also known as ...
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Non-parametric survival modelling of time to employment amongst 09/10 cohort of mathematics graduates
... for survival data analysis is one branch of mathematics that have continued to flourish in the last two ...use survival time study most extensively ...analyzing survival data developed ...
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Multistate recursively imputed survival trees for time-to-event data analysis: an application to AIDS and mortality post-HIV infection data
... developed data mining tech- nique (RSF and RIST) for multistate models (MSRSF and MSRIST) to identify important risk factors in two different stages of the ...in survival ana- lysis compared with ...
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