Results 201 to 210 of about 4,636,420 (247)

Frailty models for survival data

Lifetime Data Analysis, 1995
A frailty model is a random effects model for time variables, where the random effect (the frailty) has a multiplicative effect on the hazard. It can be used for univariate (independent) failure times, i.e. to describe the influence of unobserved covariates in a proportional hazards model.
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Comparison of models for survival data

Statistics in Medicine, 1983
AbstractMany mathematical representations are possible both for the frequency distribution of survival time and for the effect on that distribution of explanatory variables. A short review is given of the main types of model, the techniques available for model choice, the consequences of assuming a particular form and methods for assessing goodness of ...
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Adaptive Designs with Survival Data

2016
The designs with adaptive sample size modifications have been extended to survival data by several authors including application of the inverse normal method, the Fisher’s combination test approach, and some extensions of the conditional error rate principle.
Gernot Wassmer, Werner Brannath
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Survival Data of Renal Transplantations in Patients

New England Journal of Medicine, 1965
THE tabulations compiled by the Registry in Human Kidney Transplantation sponsored by the National Academy of Sciences and National Research Council and under the careful direction of Murray and his associates1 2 3 permit survival data of patients with renal grafts to be calculated by means of conventional technics.4 The published tables are based on ...
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Surviving an Avalanche of Data

Teaching Children Mathematics, 2013
Help first-grade students learn to competently generate, test, revise, and represent data before being formally taught to do so.
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Examples of Survival Data

1997
The problem of analyzing time to event data arises in a number of applied fields, such as medicine, biology, public health, epidemiology, engineering, economics, and demography. Although the statistical tools we shall present are applicable to all these disciplines, our focus is on applying the techniques to biology and medicine.
John P. Klein, Melvin L. Moeschberger
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Silencing survival data

Trends in Neurosciences, 2000
M P, Mattson, S W, Barger, R, Dantzer
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Health insurance status and cancer stage at diagnosis and survival in the United States

Ca-A Cancer Journal for Clinicians, 2022
Jingxuan Zhao, Xuesong Han, Leticia Nogueira   +2 more
exaly  

Examining the interrelationships between mindfulness‐based interventions, depression, inflammation, and cancer survival

Ca-A Cancer Journal for Clinicians, 2022
Debra Marinovic
exaly  

Combining Symptom and Survival Data

Current Problems in Cancer, 2006
Pamela J. Atherton, Sumithra J. Mandrekar, Jeff A. Sloan   +2 more
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