Search results for "probability"

Tailoring sparse multivariable regression techniques for prognostic single-nucleotide polymorphism signatures.

2011

When seeking prognostic information for patients, modern technologies provide a huge amount of genomic measurements as a starting point. For single-nucleotide polymorphisms (SNPs), there may be more than one million covariates that need to be simultaneously considered with respect to a clinical endpoint. Although the underlying biological problem cannot be solved on the basis of clinical cohorts of only modest size, some important SNPs might still be identified. Sparse multivariable regression techniques have recently become available for automatically identifying prognostic molecular signatures that comprise relatively few covariates and provide reasonable prediction performance. For illus…

An autoregressive approach to spatio-temporal disease mapping

2007

Disease mapping has been a very active research field during recent years. Nevertheless, time trends in risks have been ignored in most of these studies, yet they can provide information with a very high epidemiological value. Lately, several spatio-temporal models have been proposed, either based on a parametric description of time trends, on independent risk estimates for every period, or on the definition of the joint covariance matrix for all the periods as a Kronecker product of matrices. The following paper offers an autoregressive approach to spatio-temporal disease mapping by fusing ideas from autoregressive time series in order to link information in time and by spatial modelling t…

A comparison of some simple methods to identify geographical areas with excess incidence of a rare disease such as childhood leukaemia

1999

SUMMARY Six statistics are compared in a simulation study for their ability to identify geographical areas with a known excess incidence of a rare disease. The statistics are the standardized incidence ratio, the empirical Bayes method of Clayton and Kaldor, Poisson probability, a statistic based on the B statistics are compared for the proportion of true high-risk areas identi"ed in the top 1 per cent and 10 per cent of ranked areas. One of the PW statistics performed consistently well under all circumstances, although the results for the BT statistic were marginally better when only the top 1 per cent of ranked areas was considered. The standardized incidence ratio performed consistently …

Robust nonparametric statistical methods. Thomas P. Hettmansperger and Joseph McKean, Arnold/Wiley, London/New York, 1998. No. of pages: xi+467. Pric…

1999

Generating survival times to simulate Cox proportional hazards models by Ralf Bender, Thomas Augustin and Maria Blettner,Statistics in Medicine 2005;…

2006

Prospective analysis of infectious disease surveillance data using syndromic information.

2014

In this paper, we describe a Bayesian hierarchical Poisson model for the prospective analysis of data for infectious diseases. The proposed model consists of two components. The first component describes the behavior of disease during nonepidemic periods and the second component represents the increase in disease counts due to the presence of an epidemic. A novelty of our model formulation is that the parameters describing the spread of epidemics are allowed to vary in both space and time. We also show how syndromic information can be incorporated into the model to provide a better description of the data and more accurate one-step-ahead forecasts. These real-time forecasts can be used to …

Multi-omics HeCaToS dataset of repeated dose toxicity for cardiotoxic & hepatotoxic compounds.

2022

The data currently described was generated within the EU/FP7 HeCaToS project (Hepatic and Cardiac Toxicity Systems modeling). The project aimed to develop an in silico prediction system to contribute to drug safety assessment for humans. For this purpose, multi-omics data of repeated dose toxicity were obtained for 10 hepatotoxic and 10 cardiotoxic compounds. Most data were gained from in vitro experiments in which 3D microtissues (either hepatic or cardiac) were exposed to a therapeutic (physiologically relevant concentrations calculated through PBPK-modeling) or a toxic dosing profile (IC20 after 7 days). Exposures lasted for 14 days and samples were obtained at 7 time points (therapeutic…

Estimates of Regression Coefficients Based on the Sign Covariance Matrix

2002

SummaryA new estimator of the regression parameters is introduced in a multivariate multiple-regression model in which both the vector of explanatory variables and the vector of response variables are assumed to be random. The affine equivariant estimate matrix is constructed using the sign covariance matrix (SCM) where the sign concept is based on Oja's criterion function. The influence function and asymptotic theory are developed to consider robustness and limiting efficiencies of the SCM regression estimate. The estimate is shown to be consistent with a limiting multinormal distribution. The influence function, as a function of the length of the contamination vector, is shown to be linea…

Maximum likelihood estimation for the exponential power function parameters

1995

This paper addresses the problem of obtaining maximum likelihood estimates for the three parameters of the exponential power function; the information matrix is derived and the covariance matrix is here presented; the regularity conditions which ensure asymptotic normality and efficiency are examined. A numerical investigation is performed for exploring the bias and variance of the maximum likelihood estimates and their dependence on sample size and shape parameter.

Modeling and predicting the Spanish Bachillerato academic results over the next few years using a random network model

2016

[EN] Academic performance is a concern of paramount importance in Spain, where around of 30% of the students in the last two courses in high school, before to access to the labor market or to the university, do not achieve the minimum knowledge required according to the Spanish educational law in force. In order to analyze this problem, we propose a random network model to study the dynamics of the academic performance in Spain. Our approach is based on the idea that both, good and bad study habits, are a mixture of personal decisions and influence of classmates. Moreover, in order to consider the uncertainty in the estimation of model parameters, we perform a lot of simulations taking as t…