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Multiple-layer statistical methodology for developing data-driven models of anaerobic digestion process.

Published in Journal of environmental management

When modelling anaerobic digestion, ineffective data handling and inadequate designation of modelling parameters can undermine the model reliability. In this study, a multilayer statistical technique, which employed a machine learning technique using regression models, was introduced to systematically support the development of anaerobic digestion ...

Evidence of questionable research practices in clinical prediction models

Background: Clinical prediction models are widely used in health and medical research. The area under the receiver operating characteristic curve (AUC) is a frequently used estimate to describe the discriminatory ability of a clinical prediction model. The AUC is often interpreted relative to thresholds, with “good” or “excellent” models defined at...

The “Free lunches” index for assessing academics: a not entirely serious proposal

Background Evaluating academics is a challenge, and the use of indicators such as scientific impact (i.e. number published papers their citation rate) complex poorly validated. We propose new indicator for academic medical research: “Free lunches” index ( fl -index), computed from sum gifts industry. The -index provides direct straightforward measu...

Interpretability of statistical approaches in speech and language neuroscience

Brain functions are traditionally investigated using general linear models (GLM) in controlled experiments, which allow for a straightforward interpretation of the data. However, constraints imposed by controlled experimental setups have led neuroscientists to increasingly use machine-learning inspired approaches, which allow to work with large dat...

Learning Gaussian graphical models with latent confounders

Gaussian Graphical models (GGM) are widely used to estimate network structure in domains ranging from biology to finance. In practice, data is often corrupted by latent confounders which biases inference of the underlying true graphical structure. In this paper, we compare and contrast two strategies for inference in graphical models with latent co...

Factitious disorder imposed on self: A retrospective study of 2232 cases from health insurance databases

Objective: Patients with factitious disorder imposed on self (FDIS) seek medical care for deliberately falsified problems. Although a large amount of work has been published, the scientific literature lacks robust data on FDIS. The present study aimed to estimate the annual mean of in-hospital FDIS codings in France, describe the sociodemographic c...

A latent variable mixed-effects location scale model that also considers between-person differences in the autocorrelati...

In public health research an increasing number of studies is conducted in which intensive longitudinal data is collected in an experience sampling or a daily diary design. Typically, the resulting data is analyzed with a mixed-effects model or mixed-effects location scale model because they allow one to examine a host of interesting longitudinal re...

Statistical methods for the structural analysis of highly flexible proteins

The recognition of the functional relevance of disordered proteins has brought about a paradigm shift in Structural Biology. With the advancement of simulation methods and generative models, the scientific community now has access to atomic-resolution conformational ensembles of a large number of systems. However, the structural analysis of these o...