flexible parametric survival model
Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models
... using flexible parametric survival models to estimate the cure proportion and the survival of the “ uncured ” in a population-based ...setting. Flexible parametric ...
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Flexible parametric modelling of cause-specific hazards to estimate cumulative incidence functions
... to model compe- ting risks scenarios using the approach that estimates both the cause-specific hazards and the cumulative incidence functions as we believe both to be useful ...that parametric models have ...
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Modeling Time in Medical Education Research: The Potential of New Flexible Parametric Methods of Survival Analysis
... There are some deficits known of the Kaplan-Meier and the Cox approach. First, Kaplan-Meier as well as Cox estimates of the survivor function can be calculated only at those time points when actually at least one study ...
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Bayesian variable selection for parametric survival model with applications to cancer omics data
... namely survival analysis, plays a very important role in statistics, which arises in many fields, such as medicine, genetics, industrial engin- eering, sociology, and economics ...for parametric sur- vival ...
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Generalised linear models for flexible parametric modelling of the hazard function
... There were marked differences in the extrapolations from each model, and hence estimates of lifetime mean survival. Using external evidence, only the extrapolations from one each of the DSMs and GAMs along ...
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Predicting patient survival after deceased donor kidney transplantation using flexible parametric modelling
... predictive model that reflects current expectations of post-transplant ...restrict model development to the most recent 10 years for two main ...in survival for patients who received trans- plants ...
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Flexible Partially Linear Single Index Regression Models for Multivariate Survival Data
... multivariate survival data regression ...odds model, (iii) the generalized transformation ...index model is added to reduce the dimensions of the nonlinear covariates into a ...Weakly ...
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Generalized linear models for flexible parametric modeling of the hazard function
... Standard survival models may be insufficiently flexible to reflect the complexities of observed hazard ...more flexible models (as we have demonstrated here), it also allows for a rich class of ...
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Partitioning of excess mortality in population-based cancer patient survival studies using flexible parametric survival models
... , not randomized. Moreover, both approaches analyse the excess CVD mortality as an iso- lated condition, ignoring the fact that the excess CVD mortality is only one component of the excess mortality, and thus the ...
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Flexible modelling of survival curves for censored data
... outlines flexible strategies to model survival curves for censored data and find parametric confidence intervals using generalised lambda ...estimating survival curves: matching partial ...
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Estimating the loss of lifetime function using flexible parametric relative survival models
... relative survival, R ( t ) , was determined by a Weibull mixture cure model according to the scenarios in ...relative survival function cor- responded to a regular Weibull ...
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Survival and lifetime data analysis with a flexible class of distributions
... a parametric family of distributions with heavier tails than the normal ones; having the normal distribution as a limit case when δ → ∞ ...a parametric density function which contains a parameter that ...
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Blind Image Separation based on a Flexible Parametric Distribution Function
... combinations and generalizations such as super and generalized Gaussian mixture model (GMM) [14]. In this paper, we propose the Modified Weibull distribution (MWD) which is a modification -or we can say a ...
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A flexible approach to parametric inference in nonlinear time series models
... Ιν τερmσ οφ Θ τηε ϖαριανχε ιν τηε στατε εθυατιον ιτ ισ χεντερεδ αππροξιmατελψ οϖερ 0:1 ανδ, τηυσ, ωε αρε αλλοωινγ φορ εϖερψτηινγ φροm ϖερψ σmαλλ το mοδερατελψ λαργε σηιφτσ ιν τηε ΑΡ χοε′[r] ...
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Modelling fertility in rural South Africa with combined nonlinear parametric and semi parametric methods
... nonlinear parametric model of fertility over age by regressing the parameters of the model on these covariates using Gaussian process regres- sion, which is both nonlinear and ...the model to ...
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A comparative study of mixture cure model
... Abstract.In survival analysis, there are two types of model, parametric and ...For parametric models the survival data is described by a known non negative ...fraction. Survival ...
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Parametric models for biomarkers based on flexible size distributions
... distributions compared to GB2, confirming previous evidence that a flexible distribution is not a substitute for finding the correct distribution (Jones et al., 2014). GB2 performs reasonably well at predicting ...
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The Statistical Distribution and Determinants of Mother’s Age at First Birth
... Table 3 presents the results of the Schoenfeld residuals test of the proportionality assumption of the hazard ratio of individuals when the Cox model was fitted. A significant test statistic was obtained for some ...
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... using parametric and semi-parametric models (Cox model), mentioned factors affecting the interval between marriage and the first birth that were marriage age and women’s education ...
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How do pharmaceutical companies model survival of cancer patients? A review of NICE Single Technology Appraisals in 2017
... the survival curves were, and prevented a more quantitative ...on survival assumptions based on additional arguments or data being put forward, which were not captured by this ...of survival ...
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