When you are assessing the quality of the evidence, it’s not how the data are analyzed that’s important. Far more important is how the data are collected. Don’t agonize over whether the researchers should have used a non-parametric test or whether a random effects meta-analysis is appropriate (just to cite two obscure examples). These are important issues and they generate a lot of debate. But ...

In many situations, medical applications ask for flexible survival models that allow to extend the classical Cox-model via the inclusion of time-varying and nonparametric effects. These structured survival models are very flexible but additional difficulties arise when model choice and variable selection is desired. In particular, it has to be decided which covariates should be assigned timevar...

We suggest a method for using nonparametric information to modify a parametric model at a low-order level, retaining information in the model only to enhance the nonparametric approach at relatively high orders. Our technique represents an alternative to methods that rst t a parametric model and then adjust it. In particular, relative to a \nonparametric estimator with a parametric start," our ...

This paper presents a new approach to shape and motion estimation based on geometric primitives and relations in a model-based framework. A description of a scene in terms of structured geometric elements sharing relationships allows to derive a parametric model with Euclidian constraints, and a camera model is also proposed to reduce the problem dimensionality. It leads to a sequential MAP est...

In this article, we introduce a new generalization of the Exponentiated Exponential distribution. Various structural mathematical properties are derived. Numerical analysis for mean, variance, skewness and kurtosis dispersion index performed. The density can be right skewed symmetric with "unimodal" "bimodal" shapes. hazard function "constant", "monotonically decreasing", " monotonically increa...

According to the American Cancer Society report (1999), cancer surpasses heart disease as the leading cause of death in the United States of America (USA) for people of age less than 85. Thus, medical research in cancer is an important public health interest. Understanding how medical improvements are affecting cancer incidence, mortality and survival is critical for effective cancer control. I...

After a brief historical survey of parametric survival models, from actuarial, biomedical, demographical and engineering sources, this paper discusses the persistent reasons why parametric models still play an important role in exploratory statistical research. The phase-type models are advanced as a flexible family of latent-class models with interpretable components. These models are now supp...

6