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Algebraic Methods for Studying Interactions Between Epidemiological Variables

F. Ricceri, C. Fassino, G. Matullo, M. Roggero, M.-L. Torrente, P. Vineis, L. Terracini (2012)

Mathematical Modelling of Natural Phenomena

BackgroundIndependence models among variables is one of the most relevant topics in epidemiology, particularly in molecular epidemiology for the study of gene-gene and gene-environment interactions. They have been studied using three main kinds of analysis: regression analysis, data mining approaches and Bayesian model selection. Recently, methods of algebraic statistics have been extensively used for applications to biology. In this paper we present...

An analytical iterative statistical algorithm for image reconstruction from projections

Robert Cierniak (2014)

International Journal of Applied Mathematics and Computer Science

The main purpose of the paper is to present a statistical model-based iterative approach to the problem of image reconstruction from projections. This originally formulated reconstruction algorithm is based on a maximum likelihood method with an objective adjusted to the probability distribution of measured signals obtained from an x-ray computed tomograph with parallel beam geometry. Various forms of objectives are tested. Experimental results show that an objective that is exactly tailored statistically...

An asymptotic test for Quantitative Trait Locus detection in presence of missing genotypes

Charles-Elie Rabier (2014)

Annales de la faculté des sciences de Toulouse Mathématiques

We consider the likelihood ratio test (LRT) process related to the test of the absence of QTL (a QTL denotes a quantitative trait locus, i.e. a gene with quantitative effect on a trait) on the interval [ 0 , T ] representing a chromosome. The originality is in the fact that some genotypes are missing. We give the asymptotic distribution of this LRT process under the null hypothesis that there is no QTL on [ 0 , T ] and under local alternatives with a QTL at t ☆ on [ 0 , T ] . We show that the LRT process is asymptotically...

Análisis de duración mediante un modelo lineal generalizado semiparamétrico.

Jesús Orbe (2001)

Qüestiió

Aitkin y Clayton (1980) proponen el análisis de modelos de duración mediante modelos lineales generalizados. En este trabajo extendemos esta metodología permitiendo que el efecto de alguna de las variables explicativas pueda no ser especificado. Así, el modelo propuesto es un modelo lineal generalizado semiparamétrico, con una componente paramétrica donde se especifica la forma funcional concreta del efecto de las variables explicativas sobre la duración, y una componente no paramétrica donde recogemos...

Analysis of survey data investigating the malarial endemicity of a mixed tribal population of Bihar, India.

T. K. Basu, S. Ganguly, B. K. Sarkar, Raghunath Arnab (1998)

Qüestiió

A section of the mixed tribal population of the Singhbhum district, Bihar, India, is declared malaria epidemic zone. The tribal population of several generations is known to be suffering from malaria. A survey based on cross-sectional data analysis, was conducted on the mixed tribal population for one month. The purpose of this study was to investigate the health status using collected blood samples. The main focus is on the comparative roles of the defense mechanism and vitality factor of the human...

Aplicación de modelos de Wiener-Levy a datos biomédicos.

Charles B. Bell, F. Ramírez, E. P. Smith (1985)

Trabajos de Estadística e Investigación Operativa

Para varios conjuntos de datos biomédicos, se quiere hacer inferencia sobre la función media de la población. La mayoría de los métodos clásicos para este tipo de inferencia han sido derivados bajo el supuesto de que los datos constituyen muestras aleatorias de una población normal. Pero en realidad, en el campo médico, pocas veces se tienen muestras aleatorias. El problema práctico principal es hallar un modelo de dependencia entre los datos que aproxime la situación real y que sea manejable desde...

Application of the random field theory in PET imaging - injection dose optimization

Jiří Dvořák, Jiří Boldyš, Magdaléna Skopalová, Otakar Bělohlávek (2013)

Kybernetika

This work presents new application of the random field theory in medical imaging. Results from both integral geometry and random field theory can be used to detect locations with significantly increased radiotracer uptake in images from positron emission tomography (PET). The assumptions needed to use these results are verified on a set of real and simulated phantom images. The proposed method of detecting activation (locations with increased radiotracer concentration) is used to quantify the quality...

Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data

G. Qian, R. M. Huggins, D. Z. Loesch (2004)

Discussiones Mathematicae Probability and Statistics

An extension of the Rasch model with correlated latent variables is proposed to model correlated binary data within families. The latent variables have the classical correlation structure of Fisher (1918) and the model parameters thus have genetic interpretations. The proposed model is fitted to data using a hybrid of the Metropolis-Hastings algorithm and the MCEM modification of the EM-algorithm and is illustrated using genotype-phenotype data on a psychological subtest in families where some members...

Aspects of analysis of multivariate failure time data.

Ross L. Prentice, John D. Kalbfleisch (2003)

SORT

Multivariate failure time data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated failure time when an individual is followed for the occurrence of two or more types of events for which the individual is simultaneously at risk, or when distinct individuals have depending event times; or more complicated multistate processes where individuals may move among a number of discrete states over...

Bayesian joint modelling of the mean and covariance structures for normal longitudinal data.

Edilberto Cepeda-Cuervo, Vicente Nunez-Anton (2007)

SORT

We consider the joint modelling of the mean and covariance structures for the general antedependence model, estimating their parameters and the innovation variances in a longitudinal data context. We propose a new and computationally efficient classic estimation method based on the Fisher scoring algorithm to obtain the maximum likelihood estimates of the parameters. In addition, we also propose a new and innovative Bayesian methodology based on the Gibbs sampling, properly adapted for longitudinal...

Bayesian survival analysis based on the Rayleigh model.

Samir K. Bhattacharya, K. Tyagi Ravinder (1990)

Trabajos de Estadística

In this paper, the Bayesian analysis of the survival data arising from a Rayleigh model is carried out under the assumption that the clinical study based on n patients is terminated at the dth death, for some preassigned d (0 < d ≤ n), resulting in the survival times t1 ≤ t2 ≤ ... ≤ td, and (n - d) survivors. For the prior knowledge about the Rayleigh parameter, the gamma density, the inverted gamma density, and the beta density of the second kind are respectively assumed, and for each of...

Characterization of lung tumor subtypes through gene expression cluster validity assessment

Giorgio Valentini, Francesca Ruffino (2006)

RAIRO - Theoretical Informatics and Applications

The problem of assessing the reliability of clusters patients identified by clustering algorithms is crucial to estimate the significance of subclasses of diseases detectable at bio-molecular level, and more in general to support bio-medical discovery of patterns in gene expression data. In this paper we present an experimental analysis of the reliability of clusters discovered in lung tumor patients using DNA microarray data. In particular we investigate if subclasses of lung adenocarcinoma...

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