Emmanuel Lesaffre

Erasmus MC | Erasmus MC · Department of Bioinformatics

Li et al developed a multilevel covariance regression (MCR) model as an extension of the covariance regression model of Hoff and Niu. This model assumes a hierarchical structure for the mean and the covariance matrix. Here, we propose the combined multilevel factor analysis and covariance regression model in a Bayesian framework, simultaneously mod...

Bayesian methods to infer model dimensionality in factor analysis generally assume a lower triangular structure for the factor loadings matrix. Consequently, the ordering of the outcomes influences the results. Therefore, we propose a method to infer model dimensionality without imposing any prior restriction on the loadings matrix. Our approach co...

Background and objectives: Blood banks use a haemoglobin (Hb) threshold before blood donation to minimize donors' risk of anaemia. Hb prediction models may guide decisions on which donors to invite, and should ideally also be generally applicable, thus in different countries and settings. In this paper, we compare the outcome of various prediction...

We examine the performance of the power prior and the meta-analytic-predictive (MAP) prior for the analysis of (overdispersed) count data when multiple historical control data are incorporated into the analysis of the current data. To this end, we explore the Poisson and the negative binomial distribution. We propose a computational approach based...

We aimed to examine determinants of criminal victimization (i.e. both personal and property crime victimization) in outpatients with severe mental illness.Data was collected using a multisite epidemiological survey including a random sample of 956 adult outpatients with SMI. Data on 12-month victimization prevalence and frequency were obtained usin...

Several dynamic borrowing methods, such as the modified power prior (MPP), the commensurate prior, have been proposed to increase statistical power and reduce the required sample size in clinical trials where comparable historical controls are available. Most methods have focused on cross‐sectional endpoints, and appropriate methodology for longitu...

Combining historical control data with current control data may reduce the necessary study size of a clinical trial. However, this only applies when the historical control data are similar enough to the current control data. Several Bayesian approaches for incorporating historical data in a dynamic way have been proposed, such as the meta‐analytic‐...

We explore the performance of three popular model-selection criteria for gen-eralised linear mixed-effects models (GLMMs) for longitudinal count data (LCD). We focus on evaluating the conditional criteria (given the random effects) versus the marginal criteria (averaging over the random effects) in selecting the appropriate data-generating model. W...

Introduction To make valid comparisons across groups, a measurement instrument needs to be measurement invariant across those groups. The present study evaluates measurement invariance for experience of violence among adolescent girls and young women (AGYW) in two informal settlements in Nairobi, Kenya. Methods We used survey data collected from 1...

Mediation analysis is often used to explore the complex relationship between two variables through a third mediating variable. This paper aims to illustrate the performance of the deviance information criterion, the pseudo-Bayes factor , and the Watanabe-Akaike information criterion in selecting the appropriate multilevel mediation model. Our focus...

Devices that measure our physical, medical and mental condition have entered our daily life recently. Such devices measure our status in a continuous manner and can be useful in predicting future medical events or can guide us towards a healthier life. It is therefore important to establish that such devices record our behaviour in a reliable manne...

Mediation analysis is often used to explore the complex relationship between two variables through a third mediating variable. This paper aims to illustrate the performance of the deviance information criterion, the pseudo‐Bayes factor, and the Watanabe‐Akaike information criterion in selecting the appropriate multilevel mediation model. Our focus...

A Correction to this paper has been published: https://doi.org/10.1007/s00784-020-03725-3

Objectives An optimized oral health-related section and a video training were developed and validated for the interRAI suite of instruments. The latter is completed by professional non-dental caregivers and used in more than 40 countries to assess care needs of older adults. Methods The optimized oral health–related section (ohr-interRAI) consists...

Motivated by a longitudinal oral health study, the Signal-Tandmobiel® study, an inhomogeneous mixed hidden Markov model with continuous state-space is proposed to explain the caries disease process in children between 6 and 12 years of age. The binary caries experience outcomes are subject to misclassification. We modelled this misclassification pr...

We propose a latent linear mixed model to analyze multivariate longitudinal data of multiple ordinal variables, which are manifestations of fewer continuous latent variables. We focus on the latent level where the effects of observed covariates on the latent variables are of interest. We incorporate serial correlation into the variance component ra...

Background: While placebo-controlled randomised controlled trials remain the standard way to evaluate drugs for efficacy, historical data are used extensively across the development cycle. This ranges from supplementing contemporary data to increase the power of trials to cross-trial comparisons in estimating comparative efficacy. In many cases, t...

Background: Photographs can help non-dental professional caregivers to identify problems when inspecting the mouth of care-dependent older individuals. This study evaluated whether the assessment of oral health-related conditions presented in photographs differed between dentists and non-dental professional caregivers. Materials and methods: One...

Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary ob...

We propose a Bayesian latent Ornstein‐Uhlenbeck model to analyze unbalanced longitudinal data of binary and ordinal variables, which are manifestations of fewer continuous latent variables. We focus on the evolution of such latent variables when they continuously change over time. Existing approaches are limited to data collected at regular time in...

Increasingly complex models are being fit to data these days. This is especially the case for Bayesian modelling making use of Markov chain Monte Carlo methods. Tailored model diagnostics are usually lacking behind. This is also the case for Bayesian mediation models. In this paper, we developed a method for the detection of influential observation...

[This corrects the article DOI: 10.1371/journal.pone.0224723.].

In regression analysis, the data sample is often composed of diverse sub-populations such as ethnicities and geographical regions. In multiple application areas, it is important to identify the groups where each covariate has a positive, negative or null impact on the response. If the number of sub-populations is small, a full interaction model may...

Background Photographs might aid professional non-dental caregivers to detect problems when inspecting the mouth of care-dependent older individuals. This study evaluated whether the assessment of oral health-related conditions presented on photographs systematically differed between dentists and professional non-dental caregivers. Methods Photogr...

Introduction There are Challenges in statistically modelling immune responses to longitudinal HIV viral load exposure as a function of covariates. We define Bayesian Markov Chain Monte Carlo mixed effects models to incorporate priors and examine the effect of different distributional assumptions. We prospectively fit these models to an as-yet-unpub...

We explore the performance of three popular Bayesian model-selection criteria when vague priors are used for the covariance parameters of the random effects in a linear mixed effects model (LMM) using an extensive simulation study. In a previous paper, we have shown that the conditional selection criteria perform worse than their marginal counterpa...

Purpose: This study illustrates the huge untapped potential of quantifying the impact of culture in making meaningful comparisons across groups. Our focus is on cross-national differences in nurses' reports of their relations with physicians, and how the measurement of this complex construct and the evaluation of true differences are related to di...

Linear mixed models (LMMs) are popular to analyze repeated measurements with a Gaussian response. For longitudinal studies, the LMMs consist of a fixed part expressing the effect of covariates on the mean evolution in time and a random part expressing the variation of the individual curves around the mean curve. Selecting the appropriate fixed and...

Missing data occur in many types of studies and typically complicate the analysis. Multiple imputation, either using joint modelling or the more flexible fully conditional specification approach, are popular and work well in standard settings. In settings involving non-linear associations or interactions, however, incompatibility of the imputation...

Objectives: To explore the failure of the oral health-related section of the interRAI (ohr-interRAI), this study investigated test content validity (A.) and reasons for inaccurate assessments (B.). Background: Poor oral health negatively affects quality of life and is associated with a number of systemic diseases. The interRAI instruments, inter...

We propose a Bayesian latent vector autoregressive (LVAR) model to analyze multivariate longitudinal data of binary and ordinal variables (items) as a function of a small number of continuous latent variables. We focus on the evolution of the latent variables while taking into account the correlation structure of the responses. Often local independ...

Objective: Oral health is known to be associated with general health, but longitudinal relationships between oral health and general health indicators have not yet been fully explored in international research. Setting and participants: The sample consisted of 3 longitudinal databases: a sample from Belgium from the Protocol 3 project (n = 8359)...

Motivated by a longitudinal oral health study, the Signal-Tandmobiel® study, a Bayesian approach has been developed to model misclassified ordinal response data. Two regression models have been considered to incorporate misclassification in the categorical response. Specifically, probit and logit models have been developed. The computational diffic...

Background: Given the increased international interest in improvement strategies for patient experiences with care, it is important to understand whether the same specific care experiences affect global ratings across countries. Moreover, reporting of these global ratings currently substantially varies in both research and public reporting. Objec...

Including historical data may increase the power of the analysis of a current clinical trial and reduce the sample size of the study. Recently, several Bayesian methods for incorporating historical data have been proposed. One of the methods consists of specifying a so‐called power prior whereby the historical likelihood is downweighted with a weig...

Oral health (OH) and general health (GH) indicators are representations of the health status of the body. The OH indicators provide information about the oral health status while the GH indicators are used to assess the functional, cognitive, and mental conditions. OH is reported to be associated with GH. However, some specific associations, especi...

Genome-wide association studies (GWAS) with longitudinal phenotypes provide opportunities to identify genetic variations associated with changes in human traits over time. Mixed models are used to correct for the correlated nature of longitudinal data. GWA studies are notorious for their computational challenges, which are considerable when mixed m...

For decades, the superiority trial has been the most popular design to assess the efficacy of newly developed drugs in a randomized controlled clinical trial. In a superiority trial, the aim is to show that the new (experimental) treatment is better than the standard treatment or placebo. However, it becomes increasingly difficult to improve the ef...

Hierarchical models are extensively used in pharmacokinetics and longitudinal studies. When the estimation is performed from a Bayesian approach, model comparison is often based on the deviance information criterion (DIC). In hierarchical models with latent variables, there are several versions of this statistic: the conditional DIC (cDIC) that inc...

Although increasingly complex models have been proposed in mediation literature, there is no model nor software that incorporates the multiple possible generalizations of the simple mediation model jointly. We propose a flexible moderated mediation model allowing for (1) a hierarchical structure of clustered data, (2) more and possibly correlated m...

Early identification of contaminated food products is crucial in reducing health burdens of food-borne disease outbreaks. Analytic case-control studies are primarily used in this identification stage by comparing exposures in cases and controls using logistic regression. Standard epidemiological analysis practice is not formally defined and the com...

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware...

Studies involving large observational datasets commonly face the challenge of dealing with multiple missing values. The most popular approach to overcome this challenge, multiple imputation using chained equations, however, has been shown to be sub-optimal in complex settings, specifically in settings with longitudinal outcomes, which cannot be eas...

Purpose: To detect potentially nonlinear associations between nurses' work environment and nurse staffing on the one hand and nurse burnout on the other hand. Design: A cross-sectional multicountry study for which data collection using a survey of 33,731 registered nurses in 12 European countries took place during 2009 to 2010. Methods: A semi...

Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random interc...

Modelling the concentration of a drug in the bloodstream over time is usually done using compartment models. In pharmacokinetic data, they turn into highly nonlinear mixed-effects models (NLMEMs) when we take the heterogeneity between subjects into account. Fitting of NLMEMs can be difficult and may involve complex algorithms, with convergence crit...

Agreement is an important concept in medical and behavioral sciences, in particular in clinical decision making where disagreements possibly imply a different patient management. The concordance correlation coefficient is an appropriate measure to quantify agreement between two scorers on a quantitative scale. However, this measure is based on the...

Data of previous trials with a similar setting are often available in the analysis of clinical trials. Several Bayesian methods have been proposed for including historical data as prior information in the analysis of the current trial, such as the (modified) power prior, the (robust) meta-analytic-predictive prior, the commensurate prior and method...

Background Pre-planned futility analyses are commonly used in oncology studies. The LUME-Lung 2 study (NCT00806819; 1199.14) was stopped early based on a pre-planned, non-binding futility analysis of investigator-assessed progression-free survival (PFS), although subsequent analysis showed that the primary endpoint of improvement in centrally revie...

The Bayesian approach has become increasingly popular because it allows to fit quite complex models to data via Markov chain Monte Carlo sampling. However, it is also recognized nowadays that Markov chain Monte Carlo sampling can become computationally prohibitive when applied to a large data set. We encountered serious computational difficulties w...

Identifying the number of classes in Bayesian finite mixture models is a challenging problem. Several criteria have been proposed, such as adaptations of the deviance information criterion, marginal likelihoods, Bayes factors, and reversible jump MCMC techniques. It was recently shown that in overfitted mixture models, the overfitted latent classes...

A heterogeneous population with different clusters (K = 1, …, 6). μj = j and σj = 0.25, (j = 1, …, 6), and (Kmax = 10). Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses. A vague prior was used for the class-specific parameters. (PDF)

The results of a sensitivity analysis for fitting a more flexible model to the generated data. This analysis is based the Scenario B2 where the most flexible model (a random intercept and slope model) is fitted to data to find the true number of classes. Percentage of data sets in which the true number of clusters was found, with the mode of the es...

A heterogeneous population with different clusters (K = 1, …, 6). μj = j and σj = 0.40, (j = 1, …, 6), and (Kmax = 10). Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses. A vague prior was used for the class-specific parameters. (PDF)

Hemoglobin longitudinal data. (TXT)

A heterogeneous population with different clusters (K = 1, …, 6). μj = j and σj = 0.25, (j = 1, …, 6), and (Kmax = 10). Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses. A normal-gamma prior was used for the class-specific parameters. (PDF)

The results of a sensitivity analysis for two different sample sizes i.e., n = 100 and n = 1000. Theses analyses are based on the Scenario A2. Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses. A vague prior was used for the class-specific parameters. (PDF)

The results of a sensitivity analysis for the outlying values. This analysis is based the Scenario A1, where two extreme values added at each tail (n = 200). Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses. A vague prior was used for the class-specific parameter...

A heterogeneous population with different clusters (K = 1, …, 6). μj = j and σj = 0.40, (j = 1, …, 6), and (Kmax = 10). Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses. A normal-gamma prior was used for the class-specific parameters. (PDF)

Bugs/Jags codes to implement a univariate Gaussian mixture model with R&M criterion to find the true number of latent classes in Scenario A (R&MNI). (TIF)

The results of Scenario B1. Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses. (PDF)

Bugs/Jags codes to implement a latent class mixed-effects model with R&M criterion to find the true number of latent classes in Scenario B (R&MNI). (TIF)

Background: Migraine is much more common in females than in males, and occurrence is associated with changes in female sex hormones. Calcitonin gene-related peptide (CGRP) plays a key role in migraine, and variations in female sex hormones may affect CGRP sensitivity and/or production. Objectives: Investigate repeatability, gender differences, i...

Background: Hospital-level findings on patient experiences with care are increasingly reported publicly. A critical aspect left unexamined is the commonality of composite measures of patient experiences across different groups of patients, nursing units, hospitals, and countries. Absence of commonality is termed measurement noninvariance and is hy...