Philippe Lambert
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View article: Time-varying exogenous covariates with frequently changing values in double additive cure survival models: an application to fertility
Time-varying exogenous covariates with frequently changing values in double additive cure survival models: an application to fertility Open
Extended cure survival models enable to separate covariates that affect the long-term probability of an event (or long-term survival) from those only affecting the dynamics of events (or short-term survival). We propose to generalize the b…
View article: Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models
Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models Open
Laplace P-splines (LPS) combine the P-splines smoother and the Laplace approximation in a unifying framework for fast and flexible inference under the Bayesian paradigm. The Gaussian Markov random field prior assumed for penalized paramete…
View article: Second Birth Fertility in Germany: Social Class, Gender, and the Role of Economic Uncertainty
Second Birth Fertility in Germany: Social Class, Gender, and the Role of Economic Uncertainty Open
Building on a thick strand of the literature on the determinants of higher-order births, this study uses a gender and class perspective to analyse second birth progression rates in Germany. Using data from the German Socio-Economic Panel f…
View article: Exogenous time-varying covariates in double additive cure survival model with application to fertility
Exogenous time-varying covariates in double additive cure survival model with application to fertility Open
Extended cure survival models enable to separate covariates that affect the probability of an event (or `long-term' survival) from those only affecting the event timing (or `short-term' survival). We propose to generalize the bounded cumul…
View article: Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models
Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models Open
Laplacian-P-splines (LPS) associate the P-splines smoother and the Laplace approximation in a unifying framework for fast and flexible inference under the Bayesian paradigm. Gaussian Markov field priors imposed on penalized latent variable…
View article: Formative Assessment of Diagnostic Testing in Family Medicine with Comprehensive MCQ Followed by Certainty-Based Mark
Formative Assessment of Diagnostic Testing in Family Medicine with Comprehensive MCQ Followed by Certainty-Based Mark Open
Introduction: The choice of diagnostic tests in front of a given clinical case is a major part of medical reasoning. Failure to prescribe the right test can lead to serious diagnostic errors. Furthermore, unnecessary medical tests are a wa…
View article: Moment-based density and risk estimation from grouped summary statistics
Moment-based density and risk estimation from grouped summary statistics Open
Data on a continuous variable are often summarized by means of histograms or displayed in tabular format: the range of data is partitioned into consecutive interval classes and the number of observations falling within each class is provid…
View article: Linguistics, applied research and NLP : using NooJ in a technical-operational context. Case- study, analysis and perspectives
Linguistics, applied research and NLP : using NooJ in a technical-operational context. Case- study, analysis and perspectives Open
International audience
View article: Fast Bayesian Inference in Nonparametric Double Additive Location-Scale Models With Right- and Interval-Censored Data
Fast Bayesian Inference in Nonparametric Double Additive Location-Scale Models With Right- and Interval-Censored Data Open
Penalized B-splines are routinely used in additive models to describe smooth changes in a response with quantitative covariates. It is typically done through the conditional mean in the exponential family using generalized additive models …
View article: Inclusion of Time-Varying Covariates in Cure Survival Models with an Application in Fertility Studies
Inclusion of Time-Varying Covariates in Cure Survival Models with an Application in Fertility Studies Open
Summary Cure survival models are used when we desire to acknowledge explicitly that an unknown proportion of the population studied will never experience the event of interest. An extension of the promotion time cure model enabling the inc…
View article: Micro-scale investigation of unsaturated sand in mini-triaxial shearing using X-ray CT
Micro-scale investigation of unsaturated sand in mini-triaxial shearing using X-ray CT Open
This paper explores the micro characteristics of unsaturated sand in triaxial shearing by using X-ray computed tomography (X-ray CT). To obtain higher resolution, a mini-triaxial set-up is designed in which the sample is miniaturised to 1 …
View article: Automatic characterization of soft tissues material properties during mechanical tests
Automatic characterization of soft tissues material properties during mechanical tests Open
Introduction:The estimation of the non-linear viscoelastic characteristics of human soft tissues, such as ligaments and tendon, is often affected by the implemented procedure.This study aims at developing and validating a protocol, associa…
View article: Estimation and identification issues in the promotion time cure model when the same covariates influence long‐ and short‐term survival
Estimation and identification issues in the promotion time cure model when the same covariates influence long‐ and short‐term survival Open
The promotion time cure model is a survival model acknowledging that an unidentified proportion of subjects will never experience the event of interest whatever the duration of the follow‐up. We focus our interest on the challenges raised …
View article: Nonparametric double additive cure survival models: An application to the estimation of the non-linear effect of age at first parenthood on fertility progression
Nonparametric double additive cure survival models: An application to the estimation of the non-linear effect of age at first parenthood on fertility progression Open
This article introduces double additive models to describe the effect of continuous covariates in cure survival models, thereby relaxing the traditional linearity assumption in the two regression parts. This class of models extends the cla…
View article: Nonparametric double additive cure survival models: an application to the estimation of the nonlinear effect of age at first parenthood on fertility progression
Nonparametric double additive cure survival models: an application to the estimation of the nonlinear effect of age at first parenthood on fertility progression Open
This paper introduces double additive models to describe the effect of continuous covariates in cure survival models, thereby relaxing the traditional linear assumption in the two regression parts. This class of models extends the classica…
View article: Fertility progression in Germany: An analysis using flexible nonparametric cure survival models
Fertility progression in Germany: An analysis using flexible nonparametric cure survival models Open
Objective: This paper uses data from the German Socio-Economic Panel (GSOEP) to study the transition to second and third births. In particular, we seek to distinguish the factors that determine the timing of fertility from the factors that…
View article: Modellering van Niet-Normale Longitudinale Data in Continue Tijd, Gebaseerd op de Likelihoodfunctie
Modellering van Niet-Normale Longitudinale Data in Continue Tijd, Gebaseerd op de Likelihoodfunctie Open
We shall begin from the general fact that most of the methods proposed in the literature to analyse non-normal longitudinal data make the assumption that the observations are equally-spaced in time. Very often, the authors of such papers m…
View article: Semi-parametric frailty model for clustered interval-censored data
Semi-parametric frailty model for clustered interval-censored data Open
The shared frailty model is a popular tool to analyze correlated right-censored time-to-event data. In the shared frailty model, the latent frailty is assumed to be shared by the members of a cluster and is assigned a parametric distributi…
View article: Inference in a stochastic SIR epidemic model using Bayesian filtering, Rennes, France, 4-8 July, 2016, pp.41-46.
Inference in a stochastic SIR epidemic model using Bayesian filtering, Rennes, France, 4-8 July, 2016, pp.41-46. Open
peer reviewed
View article: Bayesian inference in an extended SEIR model with nonparametric disease transmission rate: an application to the Ebola epidemic in Sierra Leone
Bayesian inference in an extended SEIR model with nonparametric disease transmission rate: an application to the Ebola epidemic in Sierra Leone Open
The 2014 Ebola outbreak in Sierra Leone is analyzed using a susceptible-exposed-infectious-removed (SEIR) epidemic compartmental model. The discrete time-stochastic model for the epidemic evolution is coupled to a set of ordinary different…
View article: A Bayesian approach to the semiparametric estimation of a minimum inhibitory concentration distribution
A Bayesian approach to the semiparametric estimation of a minimum inhibitory concentration distribution Open
Bacteria that have developed a reduced susceptibility against antimicrobials pose a major threat to public health. Hence, monitoring their distribution in the general population is of major importance. This monitoring is performed based on…