Developed softwares and Packages

The package allows to estimate the intervention effect in cluster randomized trials (CRTs). It implements a semi-parametric GEE estimator accounting for missing data with Inverse probability weighting (IPW) and for imbalance in covariates with augmentation (AUG). The estimator IPW-AUG-GEE is Doubly robust (DR). Importantly, We exhibited that in CRTs most of the available softwares use an implementation of weights that lead to a bias in estimation if a non-independence working correlation structure is chosen. In CRTgeeDR, we solve this problem by using a different implementation of weighting while keeping the consistency properties of the IPW (and thus if the DR).

Link to the documentation

Download CRTgeeDR sources

Dissemination paper - preprint

Models based on ordinary differential equations (ODE) are a widespread tool to describe dynamical system. In biomedical sciences, data within each subject can be sparse but information is often gained from between-subjects variability. This makes natural the use of mixed effect models to estimate population parameters. Although maximum likelihood based approaches are a valuable option, both numerical and identifiability issues favor a Bayesian approach which can incorporate prior knowledge in a flexible way. However the combination of difficulties coming from the ODE system and from the presence of random effects raises a major numerical challenge. A normal approximation of the posterior can be obtained by computing the maximum of the posterior distribution (MAP).

A dedicated website to this program is available, it contains documentation and instruction of use and enables source code download.

Link to the documentation

Download N.I.M.R.O.D. Source Code Version 2.1

Dissemination paper

This algorithm provides a numerical solution to the problem of minimizing a function. This is more efficient than the Gauss-Newton-like algorithm when starting from points very far from the final minimum. A new convergence test is implemented (RDM) in addition to the usual stopping criterion : stopping rule is when the gradients are small enough in the parameters metric (GH-1G).

Link to the documentation

Download MarqLevAlg sources

Dissemination paper