Publications
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Using the inverse heat conduction problem and thermography for the determination of local heat transfer coefficients and fin effectiveness for longitudinal fins Ghent University
Heat transfer is a physical process in which energy is exchanged. It occurs in numerous applications, such as production of electricity, building climatisation, food preparation,... Since energy consumption has increased tremendously in the last decades and this trend will continue, the concept of energy efficiency has become omnipresent. In electronics miniaturization has become a trend. Desktops, laptops, dvd-players, mp3-players, ...
Analysing intensive longitudinal data after summarization at landmarks: an application to daily pain evaluation in a clinical trial Hasselt University KU Leuven
The paper addresses some of the key issues to be considered in analysing intensive longitudinal data after summarization at scheduled landmarks (i.e. prespecified times). In this context, the derivation of outcomes requires rigorous rules and the selection of covariates should be based on a thorough data exploration. To guide the choice of statistical approaches for inferences, we study the missingness mechanism by using a specific dropout ...
Two-stage model for multivariate longitudinal and survival data with application to nephrology research Hasselt University KU Leuven
In many follow-up studies different types of outcomes are collected including longitudinal measurements and time-to-event outcomes. Commonly, it is of interest to study the association between them. Joint modeling approaches of a single longitudinal outcome and survival process have recently gained increasing attention from both frequentist and Bayesian perspective. However, in many studies several longitudinal biomarkers are of interest and ...
Different methods for handling incomplete longitudinal binary outcome due to missing at random dropout Hasselt University KU Leuven
This paper compares the performance of weighted generalized estimating equations (WGEEs), multiple imputation based on generalized estimating equations (Ml-GEES) and generalized linear mixed models (GLMMs) for analyzing incomplete longitudinal binary data when the underlying study is subject to dropout. The paper aims to explore the performance of the above methods in terms of handling dropouts that are missing at random (MAR). The methods are ...
Measurement of the diffractive longitudinal structure function F(L)(D) at HERA Vrije Universiteit Brussel
First measurements are presented of the diffractive cross section I ( )ep( -> )eXY( ) at centre-of-mass energies of 225 and , together with a precise new measurement at of , using data taken with the H1 detector in the years 2006 and 2007. Together with previous H1 data at of , the measurements are used to extract the diffractive longitudinal structure function in the range of photon virtualities and fractional proton longitudinal momentum ...
Multiple-Imputation-Based Residuals and Diagnostic Plots for Joint Models of Longitudinal and Survival Outcomes Hasselt University KU Leuven
The majority of the statistical literature for the joint modeling of longitudinal and time-to-event data has focused on the development of models that aim at capturing specific aspects of the motivating case studies. However, little attention has been given to the development of diagnostic and model-assessment tools. The main difficulty in using standard model diagnostics in joint models is the nonrandom dropout in the longitudinal outcome ...
A mixed effects least squares support vector machine model for classification of longitudinal data Hasselt University KU Leuven
A mixed effects least squares support vector machine (LS-SVM) classifier is introduced to extend the standard LS-SVM classifier for handling longitudinal data. The mixed effects LS-SVM model contains a random intercept and allows to classify highly unbalanced data, in the sense that there is an unequal number of observations for each case at non-fixed time points. The methodology consists of a regression modeling and a classification step based ...
A Bivariate Pseudolikelihood for Incomplete Longitudinal Binary Data with Nonignorable Nonmonotone Missingness Hasselt University
For analyzing longitudinal binary data with nonignorable and nonmonotone missing responses, a full likelihood method is complicated algebraically, and often requires intensive computation, especially when there are many follow-up times. As an alternative, a pseudolikelihood approach has been proposed in the literature under minimal parametric assumptions. This formulation only requires specification of the marginal distributions of the responses ...