Mixture and nonmixture cure fraction models assuming discrete lifetimes: Application to a pelvic sarcoma dataset

2019 ◽  
Vol 61 (4) ◽  
pp. 813-826
Author(s):  
Ricardo Puziol de Oliveira ◽  
André F. B. Menezes ◽  
Josmar Mazucheli ◽  
Jorge A. Achcar
Keyword(s):  
Cure Fraction ◽  
Fraction Models

Bayesian cure fraction models with measurement error in the scale mixture of normal distribution

2020 ◽  
Vol 29 (9) ◽  
pp. 2411-2444
Author(s):  
Anna R S Marinho ◽  
Rosangela H Loschi
Keyword(s):  
Measurement Error ◽  
Normal Distribution ◽  
Measurement Errors ◽  
Error Variance ◽  
Scale Mixture ◽  
Time To Event Data ◽  
Proposed Model ◽  
Cure Fraction ◽  
Measurement Error Variance ◽  
Fraction Models

Cure fraction models have been widely used to model time-to-event data when part of the individuals survives long-term after disease and are considered cured. Most cure fraction models neglect the measurement error that some covariates may experience which leads to poor estimates for the cure fraction. We introduce a Bayesian promotion time cure model that accounts for both mismeasured covariates and atypical measurement errors. This is attained by assuming a scale mixture of the normal distribution to describe the uncertainty about the measurement error. Extending previous works, we also assume that the measurement error variance is unknown and should be estimated. Three classes of prior distributions are assumed to model the uncertainty about the measurement error variance. Simulation studies are performed evaluating the proposed model in different scenarios and comparing it to the standard promotion time cure fraction model. Results show that the proposed models are competitive ones. The proposed model is fitted to analyze a dataset from a melanoma clinical trial assuming that the Breslow depth is mismeasured.

scholarly journals Mixture and Non-Mixture Cure Fraction Models Based on Generalized Gompertz Distribution under Bayesian Approach

2016 ◽  
Vol 66 (1) ◽  
pp. 121-135 ◽  
Author(s):  
Prafulla Kumar Swain ◽  
Gurprit Grover ◽  
Komal Goel
Keyword(s):  
Monte Carlo ◽  
Censored Data ◽  
Bayesian Approach ◽  
New Drugs ◽  
Lifetime Data ◽  
Gompertz Distribution ◽  
Cure Fraction ◽  
Long Term Survivors ◽  
Fraction Models

Abstract The cure fraction models are generally used to model lifetime data with long term survivors. In a cohort of cancer patients, it has been observed that due to the development of new drugs some patients are cured permanently, and some are not cured. The patients who are cured permanently are called cured or long term survivors while patients who experience the recurrence of the disease are termed as susceptibles or uncured. Thus, the population is divided into two groups: a group of cured individuals and a group of susceptible individuals. The proportion of cured individuals after the treatment is typically known as the cure fraction. In this paper, we have introduced a three parameter Gompertz (viz. scale, shape and acceleration) or generalized Gompertz distribution in the presence of cure fraction, censored data and covariates for estimating the proportion of cure fraction through Bayesian Approach. Inferences are obtained using the standard Markov Chain Monte Carlo technique in openBUGS software.

Two-Phase Friction Factor Obtained From Various Void Fraction Models During Condensation of R134A in Vertical Downward Flow at High Mass Flux

2008 ◽  
Author(s):  
Ahmet Selim Dalkilic ◽  
Suriyan Laohalertdecha ◽  
Somchai Wongwises
Keyword(s):  
Void Fraction ◽  
Annular Flow ◽  
Smooth Tube ◽  
High Mass ◽  
Two Phase ◽  
Void Fractions ◽  
Mass Fluxes ◽  
Friction Factors ◽  
Flow Void ◽  
Fraction Models

Void fractions are determined in vertical downward annular two-phase flow of R134a inside 8.1 mm i.d. smooth tube. The experiments are done at average saturated condensing temperatures of 40 and 50°C. The average qualities are between 0.84–0.94. The mass fluxes are around 515 kg m−2s−1. The experimental setup is explained elaborately. Comparisons between the void fraction determined from 35 void fraction correlations are done. According to the use of various horizontal and vertical annular flow void fraction models together with the present experimental condensation heat transfer data, similar void fraction results were obtained mostly for the smooth tube. The experimental friction factors obtained from void fraction correlations are compared with the friction factors determined from graphical information provided by Bergelin et. al. Effect of void fraction alteration on the momentum pressure drop is also presented.

Vertical modeling: analysis of competing risks data with a cure fraction

2018 ◽  
Vol 25 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Mioara Alina Nicolaie ◽  
Jeremy M. G. Taylor ◽  
Catherine Legrand
Keyword(s):  
Competing Risks ◽  
Modeling Analysis ◽  
Cure Fraction ◽  
Competing Risks Data

Evaluation of the tail of the probability distribution of daily and sub-daily precipitation in CMIP6 models

2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen
Keyword(s):  
General Circulation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Coupled Model ◽  
Lower Troposphere ◽  
General Circulation Models ◽  
Intercomparison Project ◽  
Cloud Tops ◽  
The Tropics ◽  
Fraction Models

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.

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