Now showing items 39-58 of 59

• Optimal experimental design for cytogenetic dose-response calibration curves ﻿

(2019)
Purpose: To introduce optimal experimental design techniques in the cytogenetic biological dosimetry practice. This includes the development of a new optimality criterion for the calibration of radiation doses. Materials ...
• Penalized composite link mixed models for two-dimensional count data ﻿

(2015-05)
Mortality data provide valuable information for the study of the spatial distribution of mortality risk, in disciplines such as spatial epidemiology, medical demography, and public health. However, they are often available ...
• Penalized composite link models for aggregated spatial count data: a mixed model approach ﻿

(2016-01-01)
Mortality data provide valuable information for the study of the spatial distri- bution of mortality risk, in disciplines such as spatial epidemiology and public health. However, they are frequently available in an aggregated ...
• Poisson excess relative risk models: New implementations and software ﻿

(2019-03-01)
Two new implementations for fitting Poisson excess relative risk methods are proposed for assumed simple models. This allows for estimation of the excess relative risk associated with a unique exposure, where the background ...
• Predicting Pregnancy Outcomes Using Longitudinal Information: A Penalized Splines Mixed–Effects Model Approach ﻿

(2017-02-09)
We propose a semiparametric mixed–effects model (SNMM) using penalized splines to clas- sify longitudinal data and improve the prediction of a binary outcome. The work is motivated by a study in which different hormone ...
• Predictive factors over time of health-related quality of life in chronic obstructive pulmonary disease patients ﻿

(2020-01)
Background: Health-related quality of life (HRQoL) should be seen as a tool that provides an overall view of the general clinical condition of a COPD patient. The aims of this study were to identify variables associated ...
• Predictors of one and two years’ mortality in patients with colon cancer: a prospective cohort study ﻿

(2018)
Tools to aid in the prognosis assessment of colon cancer patients in terms of risk of mortality are needed. Goals of this study are to develop and validate clinical prediction rules for 1-and 2-year mortality in these ...
• Robust combination of the Morris and Sobol methods in complex multidimensional models ﻿

(2019)
Conducting global sensitivity analysis using variance decomposition methods in complex simulation models with many input factors is usually unaffordable. An alternative is to first apply a screening method to reduce the ...
• Sample size impact on the categorisation of continuous variables in clinical prediction ﻿

(2017-12)
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous predictor ...
• A simple Bayesian linear excess relative risk model ﻿

(2017-07-11)
A new Bayesian Poisson relative risk model is proposed for displaying the excess relative risk associated to a unique exposure as a probability distribution in a closed form. The background risk can be modelled by a unique ...
• Simulation approach for assessing the performance of the γEWMA control chart ﻿

(2021-02-22)
i) Purpose: The purpose of this paper is to evaluate the performance of a modified EWMA control chart ($\gamma$EWMA control chart), which considers data distribution and incorporate its correlation structure, simulating ...
• Smooth additive mixed models for predicting aboveground biomass ﻿

(2016-12-01)
Aboveground biomass estimation in short-rotation forestry plantations is an essential step in the development of crop management strategies as well as allowing the economic viability of the crop to be determined prior to ...
• Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) ﻿

(2020)
The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. ...
• Spatial Models for Field Trials ﻿

(2016-09-01)
An important aim of the analysis of agricultural field trials is to obtain good predictions for genotypic performance, by correcting for spatial effects. In practice these corrections turn out to be complicated, since there ...
• Spatio-temporal adaptive penalized splines with application to Neuroscience ﻿

(2016-12-30)
Data analysed here derive from experiments conducted to study neurons' activity in the visual cortex of behaving monkeys. We consider a spatio-temporal adaptive penalized spline (P-spline) approach for modelling the firing ...
• Spatio-temporal functional data analysis for wireless sensor networks data ﻿

(2015-05-05)
A new methodology is proposed for the analysis, modeling, and forecasting of data collected from a wireless sensor network. Our approach is considered in the framework of a functional data-analysis paradigm where observed ...
• A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay ﻿

(2018-11-28)
Over the last decade, the γ–H2AX focus assay, which exploits the phosphorylation of the H2AX histone following DNA double–strand–breaks, has made considerable progress towards acceptance as a reliable biomarker for exposure ...
• Suggestion of reduced cancer risks following cardiac x-ray exposures is unconvincing ﻿

(2018-03-31)
• Time resolved amplified FRET identifies protein kinase B activation state as a marker for poor prognosis in clear cell renal cell carcinoma ﻿

(2017-12)
Purpose Clear cell Renal Cell Carcinomas (ccRCC), the largest group of renal tumours, are resistant to classical therapies. The determination of the functional state of actionable biomarkers for the assessment of these ...
• Time-varying coefficient estimation in SURE models. Application to portfolio management. ﻿

(2017-01-01)
This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. ...