References of "Lambert, Philippe"
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See detailBayesian penalized smoothing approaches in models specified using affine differential equations with unknown error distributions
Jaeger, Jonathan ULg; Lambert, Philippe ULg

in Journal of Applied Statistics (in press)

A full Bayesian approach based on ODE-penalized B-splines and penalized Gaussian mixture is proposed to jointly estimate ODE-parameters, state function and error distribution from the observation of some ... [more ▼]

A full Bayesian approach based on ODE-penalized B-splines and penalized Gaussian mixture is proposed to jointly estimate ODE-parameters, state function and error distribution from the observation of some state functions involved in systems of affine differential equations. Simulations inspired by pharmacokinetic studies show that the proposed method provides comparable results to the method based on the standard ODE-penalized B-spline approach (i.e. with the Gaussian error distribution assumption) and outperforms the standard ODE-penalized B-splines when the distribution is not Gaussian. This methodology is illustrated on the Theophylline dataset. [less ▲]

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See detailEstimation and approximation in nonlinear dynamic systems using quasilinearization
Frasso, Gianluca ULg; Jaeger, Jonathan ULg; Lambert, Philippe ULg

E-print/Working paper (2014)

Nonlinear (systems of) ordinary differential equations (ODEs) are common tools in the analysis of complex one-dimensional dynamic systems. In this paper we propose a smoothing approach regularized by a ... [more ▼]

Nonlinear (systems of) ordinary differential equations (ODEs) are common tools in the analysis of complex one-dimensional dynamic systems. In this paper we propose a smoothing approach regularized by a quasilinearized ODE-based penalty in order to approximate the state functions and estimate the parameters defining nonlinear differential systems from noisy data. Within the quasilinearized spline based framework, the estimation process reduces to a conditionally linear problem for the optimization of the spline coefficients. Furthermore, standard ODE compliance parameter(s) selection criteria are easily applicable and conditions on the state function(s) can be eventually imposed using soft or hard constraints. The approach is illustrated on real and simulated data. [less ▲]

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See detailSpline approximation to conditional Archimedean copula
Lambert, Philippe ULg

in Stat (2014), 3(1), 200-217

We propose a flexible copula model to describe changes with a covariate in the dependence structure of (conditionally exchangeable) random variables. The starting point is a spline approximation to the ... [more ▼]

We propose a flexible copula model to describe changes with a covariate in the dependence structure of (conditionally exchangeable) random variables. The starting point is a spline approximation to the generator of an Archimedean copula. Changes in the dependence structure with a covariate x are modelled by flexible regression of the spline coefficients on x. The performances and properties of the spline estimate of the reference generator and the abilities of these conditional models to approximate conditional copulas are studied through extensive simulations. Inference is made using Bayesian arguments with posterior distributions explored using importance sampling or adaptive MCMC algorithms. The modelling strategy is illustrated with the analysis of bivariate growth curve data. [less ▲]

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See detailSemiparametric Bayesian frailty model for clustered interval-censored data
Cetinyürek, Aysun ULg; Lambert, Philippe ULg

Report (2014)

The shared frailty model is one of the 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 ... [more ▼]

The shared frailty model is one of the 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 distribution, typically, a gamma distribution due to its conjugacy. However, in case of interval-censored time-to-event data, the inclusion of gamma frailties results in complicated intractable likelihoods, where the conjugacy property does not hold anymore. Here, we propose a semiparametric Bayesian frailty model for analyzing such data. We discuss three parametric specifications for frailty distribution in the analysis of interval-censored data. Afterwards we call particular attention to nonparametric specification of the frailty distribution. The results of the simulation study suggest that the proposed approach is robust to misspecification of the frailty distribution. Moreover, the performance of the proposed methodology is quite good in practical situations where the frailty distribution is multimodal or skewed. The approach is applied to dental data arising from the Signal Tandmobiel Study. [less ▲]

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See detailSimulation-based study comparing multiple imputation methods for non-monotone missing ordinal data in longitudinal settings
Donneau, Anne-Françoise ULg; Mauer, Murielle; Lambert, Philippe ULg et al

in Journal of Biopharmaceutical Statistics (2014)

The application of multiple imputation (MI) techniques as a preliminary step to handle missing values in data analysis is well established. The MI method can be classified into two broad classes, the ... [more ▼]

The application of multiple imputation (MI) techniques as a preliminary step to handle missing values in data analysis is well established. The MI method can be classified into two broad classes, the joint modeling and the fully conditional specification approaches. Their relative performance for the longitudinal ordinal data setting under the missing at random (MAR) assumption is not well documented. This paper intends to fill this gap by conducting a large simulation study on the estimation of the parameters of a longitudinal proportional odds model. The two MI methods are also illustrated in quality of life data from a cancer clinical trial. [less ▲]

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See detailFlexible estimation in cure survival models using Bayesian P-splines
Bremhorst, Vincent; Lambert, Philippe ULg

in Computational Statistics & Data Analysis (2014)

In the analysis of survival data, it is usually assumed that any unit will experience the event of interest if it is observed for a sufficiently long time. However, it can be explicitly assumed that an ... [more ▼]

In the analysis of survival data, it is usually assumed that any unit will experience the event of interest if it is observed for a sufficiently long time. However, it can be explicitly assumed that an unknown proportion of the population under study will never experience the monitored event. The promotion time model, which has a biological motivation, is one of the survival models taking this feature into account. The promotion time model assumes that the failure time of each subject is generated by the minimum of N independent latent event times with a common distribution independent of N. An extension which allows the covariates to influence simultane- ously the probability of being cured and the latent distribution is presented. The latent distribution is estimated using a flexible Cox proportional hazard model where the logarithm of the baseline hazard function is specified using Bayesian P-splines. Introducing covariates in the latent distribution implies that the population hazard function might not have a proportional hazard structure. However, the use of P- splines provides a smooth estimation of the population hazard ratio over time. The identification issues of the model are discussed and a restricted use of the model when the follow up of the study is not sufficiently long is proposed. The accuracy of our methodology is evaluated through a simulation study and the model is illustrated on data from a Melanoma clinical trial. [less ▲]

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See detailInflated discrete Beta regression models for Likert and discrete rating scale outcomes
Taverne, Cédric; Lambert, Philippe ULg

E-print/Working paper (2014)

Discrete ordinal responses such as Likert scales are regularly proposed in questionnaires and used as dependent variable in modeling. The response distribution for such scales is always discrete, with ... [more ▼]

Discrete ordinal responses such as Likert scales are regularly proposed in questionnaires and used as dependent variable in modeling. The response distribution for such scales is always discrete, with bounded support and often skewed. In addition, one particular level of the scale is frequently inflated as it cumulates respondents who invari- ably choose that particular level (typically the middle or one extreme of the scale) without hesitation with those who chose that alternative but might have selected a neighboring one. The inflated discrete beta regression (IDBR) model addresses those four critical characteristics that have never been taken into account simultaneously by existing models. The mean and the dispersion of rates are jointly regressed on covariates using an underlying beta distribution. The probability that choosers of the inflated level invariably make that choice is also regressed on covariates. Simulation studies used to evaluate the statistical properties of the IDBR model suggest that it produces more precise predictions than competing models. The ability to jointly model the location and dispersion of (the distribution of) an ordinal response, as well as to characterize the profile of subject selecting an ”inflated” alternative are the most relevant features of the IDBR model. It is illustrated with the analysis of the political positioning on a ”left-right” scale of the Belgian respondents in the 2012 European Social Survey. [less ▲]

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See detailEstimation and approximation in multidimensional dynamics
Frasso, Gianluca ULg; Jaeger, Jonathan ULg; Lambert, Philippe ULg

E-print/Working paper (2013)

Differential equations (DEs) are commonly used to describe dynamic systems evolving in one (ordinary differential equations or ODEs) or in more than one dimensions (partial differential equations or PDEs ... [more ▼]

Differential equations (DEs) are commonly used to describe dynamic systems evolving in one (ordinary differential equations or ODEs) or in more than one dimensions (partial differential equations or PDEs). In real data applications the parameters involved in the DE models are usually unknown and need to be estimated from the available measurements together with the state function. In this paper, we present frequentist and Bayesian approaches for the joint estimation of the parameters and of the state functions involved in PDEs. We also propose two strategies to include differential (initial and/or boundary) conditions in the estimation procedure. We evaluate the performances of the proposed strategy on simulated and real data applications. [less ▲]

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See detailSpline approximation to conditional Archimedean copula
Lambert, Philippe ULg

E-print/Working paper (2013)

We propose a flexible copula model to describe changes with a covari- ate in the dependence structure of (conditionally exchangeable) random variables. The starting point is a spline approximation to the ... [more ▼]

We propose a flexible copula model to describe changes with a covari- ate in the dependence structure of (conditionally exchangeable) random variables. The starting point is a spline approximation to the generator of an Archimedean copula. Changes in the dependence structure with a covariate x are modelled by flexible regression of the spline coefficients on x. The performances and properties of the spline estimate of the reference generator and the abilities of these conditional models to approximate conditional copulas are studied through simulations. Inference is made using Bayesian arguments with posterior distributions explored using im- portance sampling or adaptive MCMC algorithms. The modelling strategy is illustrated with two examples. [less ▲]

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See detailBayesian P-spline estimation in hierarchical models specified by systems of affine differential equations
Jaeger, Jonathan ULg; Lambert, Philippe ULg

in Statistical Modelling : An International Journal (2013), 13

Ordinary differential equations (ODEs) are widely used to model physical, chemical and biological processes. Current methods for parameter estimation can be computationally intensive and/or not suitable ... [more ▼]

Ordinary differential equations (ODEs) are widely used to model physical, chemical and biological processes. Current methods for parameter estimation can be computationally intensive and/or not suitable for inference and prediction. Frequentist approaches based on ODE-penalized smoothing techniques have recently solved part of these drawbacks. A full Bayesian approach based on ODE-penalized B-splines is proposed to jointly estimate ODE parameters and state functions from affine systems of differential equations. Simulations inspired by pharmacokinetic studies show that the proposed method provides comparable results to methods based on explicit solution of the ODEs and outperforms the frequentist ODE-penalized smoothing approach. The basic model is extended to a hierarchical one in order to study cases where several subjects are involved. This Bayesian hierarchical approach is illustrated on real data for the study of perfusion ratio after a femoral artery occlusion. Model selection is feasible through the analysis of the posterior distributions of the ODE adhesion parameters and is illustrated on a real pharmacokinetic dataset. [less ▲]

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See detailA Bayesian Design Space for analytical methods based on multivariate models and predictions
Lebrun, Pierre ULg; Boulanger, Bruno ULg; Debrus, Benjamin ULg et al

in Journal of Biopharmaceutical Statistics (2013), 23

The International Conference for Harmonization (ICH) has released regulatory guidelines for Pharmaceutical Development. In the document ICH Q8, The Design Space of a process is presented as the set of ... [more ▼]

The International Conference for Harmonization (ICH) has released regulatory guidelines for Pharmaceutical Development. In the document ICH Q8, The Design Space of a process is presented as the set of factor settings providing satisfactory results. However, ICH Q8 does not propose any practical methodology to define, derive and compute Design Space. In parallel, in the last decades, it has been observed that the diversity and the quality of analytical methods have evolved exponentially allowing substantial gains in selectivity and sensitivity. However, there is still a lack for a rationale towards the development of robust separation methods in a systematic way. Applying ICH Q8 to analytical methods provides a methodology for predicting a region of the space of factors in which results will be reliable. Combining design of experiments and Bayesian standard multivariate regression, an identified form of the predictive distribution of a new response vector has been identified and used, under non-informative as well as informative prior distributions of the parameters. From the responses and their predictive distribution, various critical quality attributes can be easily derived. This Bayesian framework was then extended to the multi-criteria setting to estimate the predictive probability that several critical quality attributes will be jointly achieved in the future use of an analytical method. An example based on a high-performance liquid chromatography (HPLC) method is given. For this example, a constrained sampling scheme was applied to ensure the modeled responses have desirable properties. [less ▲]

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See detailNonparametric additive location-scale models for interval censored data
Lambert, Philippe ULg

in Statistics and computing (2013), 23

An nonparametric additive model for the location and dispersion of a continuous response with an arbitrary smooth conditional distribution is proposed. B-splines are used to specify the three components ... [more ▼]

An nonparametric additive model for the location and dispersion of a continuous response with an arbitrary smooth conditional distribution is proposed. B-splines are used to specify the three components of the model. It can deal with interval censored data and multiple covariates. After a simulation study, the relation between age, the number of years of full-time education and the net income (provided as intervals) available per person in Belgian households is studied from survey data. [less ▲]

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See detailBayesian ODE-penalized B-spline model with Gaussian mixture as error distribution
Jaeger, Jonathan ULg; Lambert, Philippe ULg

Scientific conference (2012, July 18)

In the standard Bayesian ODE-penalized B-spline approach, it is assumed that the error distribution is homogeneous Gaussian. But, in many applications, the normal assumption for the error distribution is ... [more ▼]

In the standard Bayesian ODE-penalized B-spline approach, it is assumed that the error distribution is homogeneous Gaussian. But, in many applications, the normal assumption for the error distribution is not a realistic choice. The goal of this paper is to extend the standard Bayesian ODE-penalized B-spline approach to settings where the error term distribution can be described using a mixture of normals. [less ▲]

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See detailOn the use of adhesion parameters to validate models specified using systems of affine differential equations
Jaeger, Jonathan ULg; Lambert, Philippe ULg

E-print/Working paper (2012)

A strategy for the selection of system of differential equations is proposed based on Bayesian ODE-penalized B-spline approach. It estimates the ODE parameters, approximates the solution of the ODE model ... [more ▼]

A strategy for the selection of system of differential equations is proposed based on Bayesian ODE-penalized B-spline approach. It estimates the ODE parameters, approximates the solution of the ODE model and quantifies the suitability of the proposed differential equations to model the dynamics of the observed state functions. Simulation study confirms that these ODE-adhesion parameters are able to question a system of differential equations as a descriptor of the dynamics in the state functions. This methodology is illustrated on a pharmacokinetic study. [less ▲]

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See detailTesting conditional asymmetry: a residual-based approach
Lambert, Philippe ULg; Laurent, Sébastien; Veredas, Davis

in Journal of Economic Dynamics & Control (2012), 36

We propose three residual-based tests for conditional asymmetry. The distribution is assumed to fall into the class of skewed distributions of Fernandez and Steel (1998). In this class, asymmetry is ... [more ▼]

We propose three residual-based tests for conditional asymmetry. The distribution is assumed to fall into the class of skewed distributions of Fernandez and Steel (1998). In this class, asymmetry is measured by the ratio between the probabilities of being larger and smaller than the mode. Estimation is performed under the null hypothesis of constant asymmetry of the innovations and, in a second step, tests for conditional asymmetry are performed on generalized residuals through parametric and non- parametric methods. We derive the asymptotic distribution of the tests that incorporates the uncertainty of the estimated parameters. A Monte Carlo study shows that neglecting this uncertainty severely biases the tests. An empirical application on a basket of daily returns reveals that financial data often present dynamics in the conditional skewness. [less ▲]

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See detailEfficacy of pre-ascent climbing route visual inspection in indoor sport climbing
Sanchez, Xavier; Lambert, Philippe ULg; Jones, G. et al

in Scandinavian Journal of Medicine & Science in Sports (2012), 22

Pre-ascent climbing route visual inspection (route preview) has been suggested as a key climbing performance para- meter although its role has never been verified experimentally. We examined the efficacy ... [more ▼]

Pre-ascent climbing route visual inspection (route preview) has been suggested as a key climbing performance para- meter although its role has never been verified experimentally. We examined the efficacy of this perceptual-cognitive skill on indoor sport climbing performance. Twenty-nine male climbers, divided into intermediate, advanced and expert climbing level groups, climbed two indoor sport routes matching their climbing level and, where applicable, routes below their climbing level. At each level, one route was climbed with a preview, where participants benefited from a 3-min pre-ascent climbing route visual inspection. Performance was assessed in terms of output (route comple- tion) and form (number and duration of moves and stops). Route preview did not influence the output performance. Climbers using visual inspection were no more likely to finish the ascent than those without the option of using visual inspection. Conversely, route preview did influence form performance; climbers made fewer, and shorter stops during their ascent following a preview of the route. Form performances differences remained when baseline ability levels were taken into account, although for shorter duration of stops only with expert climbers benefiting most from route preview. The ability to visually inspect a climb before its ascent may represent an essential component of performance optimization. [less ▲]

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See detailSmooth estimation of survival functions and hazard ratios from interval-censored data using Bayesian penalized B-splines
Cetinyürek, Aysun ULg; Lambert, Philippe ULg

in Statistics in Medicine (2011), 30(1), 75-90

We discuss the use of Bayesian P-spline and of the composite link model to estimate survival functions and hazard-ratios from interval-censored data. If one further assumes proportionality of the hazards ... [more ▼]

We discuss the use of Bayesian P-spline and of the composite link model to estimate survival functions and hazard-ratios from interval-censored data. If one further assumes proportionality of the hazards, the proposed strategy provides a smoothed estimate of the baseline hazard along with estimates of global covariate effects. The frequentist properties of our Bayesian estimators are assessed by an extensive simulation study. We further illustrate the methodology by two examples showing that the proportionality of the hazards might also be found inappropriate from interval-censored data. [less ▲]

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See detailComments on: Inference in multivariate Archimedean copulas models
Lambert, Philippe ULg

in Test (2011), 20

Detailed reference viewed: 20 (0 ULg)