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BioStat - ISSN 2632-8291 - © ISTE Ltd
The Biostatistics and Health Sciences journal focuses on statistics applied to clinical, epidemiologic, economic, psychological and sociological research, in medical biology. It publishes in priority articles written in French and English.
The aim of this journal is to make biostatistics and its application to human health issues go forward in its medical, economical, psychological and biological dimensions.
The papers can be of different types:
Methodological development works:
- the work should emphasize the development of new statistical methods applied to health sciences;
- an introduction describing the application and scientific objectives on which the new methods are concentrated and a discussion about the theoretical results on the basis of real data illustrating the issues is strongly advised;
- mathematical demonstrations, if provided, may be presented in the body of the article or as an appendix.
Innovative applications of existing statistical methods to data or real health problems:
- such applications, usually complex methods or a complex combination of simple methods, must be original;
- an introduction describing the application and scientific objectives of the actual study, of which data are analyzed, and a discussion section of the results are strongly advised.
Journal papers providing an overview of a specific area of biostatistic research in health science:
- the aim of these works will be to sum up the scientific results obtained in health science through biostatistics and/or recent methodological developments in this field;
- These papers may include an important aspect of popularizing knowledge for researchers and health professionals;
- French doctoral students and researchers in the health field and, more generally francophones, are strongly encouraged to submit their work.
Biostatistiques et sciences de la santé s’intéresse à la statistique appliquée à la recherche clinique et épidémiologique, en économie, en psychologie et sociologie de la santé, en biologie médicale etc. Elle publie prioritairement des articles écrits en français, et des articles en anglais.
L’objectif de cette revue est de faire avancer la biostatistique et son application à des problèmes de santé, dans ses dimensions médicale, économique, psychologique, sociologique et biologique etc.
Les articles peuvent être de différents types :
Des travaux de développement méthodologique :
- les travaux doivent mettre l’accent sur le développement de nouvelles méthodes statistiques appliquées aux sciences de la santé ;
- une introduction décrivant l’application et les objectifs scientifiques sur lesquels les nouvelles méthodes se concentrent, ainsi qu’une discussion des résultats théoriques à partir de données réelles illustrant les questions abordées est vivement conseillée ;
- les démonstrations mathématiques, si elles sont fournies, peuvent être présentées dans le corps de l’article ou en annexe.
Des applications innovantes de méthodes statistiques existantes à des données ou des problématiques réelles de la santé :
- de telles applications, le plus souvent de méthodes complexes ou de combinaison complexe de méthodes simples doivent être originales ;
- une introduction décrivant l’application et les objectifs scientifiques de l’étude réelle, dont les données sont analysées, et une section discussion des résultats sont vivement conseillées.
Des articles de revue dressant un état des lieux dans un domaine particulier de la recherche biostatitique en science de la santé :
- l’objectif de ces travaux sera de synthétiser les résultats scientifiques obtenus en sciences de la santé grâce à la biostatistique et/ou les développements méthodologiques récents de ce domaine ;
- ces articles pourront comprendre un aspect important de vulgarisation des connaissances à destination des chercheurs et des professionnels de la santé ;
- les doctorants et chercheurs en santé français et plus généralement francophones, sont vivement encouragés à soumettre leurs travaux.
This paper discusses state-space models with multi-categorical longitudinal observations and states characterized by the so-called Conditional Heteroskedastic AutoRegressive Nonlinear (CHARN) models. The latter are estimated via generalized Kalman recursions based on particle filters and EM algorithm. Our findings generalize the literature. They are illustrated by numerical simulations and applied to data from patients surged for breast cancer.
In this paper, we present some parametric families of probability distributions associated to particular single type homogeneous branching processes in continuous time. Their simplicity and the relevance of the interpretation of parameters for many domains of applications are of valuable interest for statistical inference. These families are particularly well adapted to handle branching dynamical systems of populations where Poisson assumption is generally but mistakenly assumed. Calculations and pertinent properties concerning these probability distributions are derived from their generating functions satisfying specific linear partial differential equations. As a by product, these equations allow the statement of a general recurrence formula for factorial moments.
In this paper, we present a latent based method to model the longitudinal evolution of Health related quality of life of patients under specific survey conditions. First of all, we will deal with the frequent issue when different questionnaires are sequentially used to measure the same latent trait during a long follow up time. Secondly, we propose models allowing the latent process to potentially behave under a long range memory constraint as the quality of life of an individual can highly depend on his or her far antecedents. For that purpose, we constructed a general statistical framework and gave the corresponding likelihood formula. Then, we developed an approximation algorithm for the likelihood, within the R-software, and applied it to a real data set. The statistical results obtained for this data set substantiate the following points : The pertinence of this approach concerning some rational testing hypotheses, the compliance of the parameter estimate values as well as it robustness with respect to measurement protocol changes.
Child malnutrition remains a major public health problem around the world, particularly in Africa. In Cameroon, for example, the Demographic and Health Survey (DHS), carried out in 2018, shows that three out of ten children under five are victims of malnutrition. The objective of this study is to find the individual, family and community factors associate with this phenomenon. The methodology used to achieve it relies mainly on data from the abovementioned survey and the multivariate multilevel models. The results of the study showed that, all things being equal, the children most affected by malnutrition are those whose two parents are uneducated or poorly educated and whose mothers are not exposed to media and autonomy in decision-making. These children are male, have already celebrated their first birthday, were born with a low weight, were recently anemic or ill and are separated from their previous siblings by less than 24 months. Likewise, the results of the study revealed that these children live in poor households and in ethnically homogeneous communities and these have no or little exposure to media. In view of the inter-community and intra-community variances, individual and family characteristics are the factors which most explain the variation in child malnutrition in the studied milieu. Future interventions in this area should take into account the factors highlighted in this study.
Anemia is one of the most common and difficult nutritional problems in the world. The 2011 WHO suggests that anemia has affected approximately 800 million children and women. More than half of the children in the South-East Asia and Africa Regions (53.8% or more) are anemic, with the highest proportion (62.3%) coming from the African Region. The World Bank estimates its prevalence among children in sub-Saharan Africa at 67.8%, with 63.9% in Central Africa. WHO and UNICEF stress the urgency of combating it and emphasize the importance of recognizing its multifactorial etiology, a prerequisite for the implementation of effective control programs.
In this article, we show that structure validity is an essential step in the psychometric validation of subjective measurement scales, the partial credit model is used to study the structure validity. We take as an example, the psychometric validation of the GOHAI scale (General Oral Health Assessment Index) for the general French population. The partial credit model verifies the unidimensionality of the GOHAI scale.
Editorial Board
Editor in Chief
Mounir MESBAH
LSTA
Sorbonne Université
mounir.mesbah@upmc.fr
Co-Editors
Jean-François DUPUY
INSA de Rennes
Université de Rennes 1
jean-francois.dupuy@insa-rennes.fr
Philippe BROET
INSERM
philippe.broet@inserm.fr
Jean-Benoit HARDOUIN
Université de Nantes
jean-benoit.hardouin@univ-nantes.fr
Hélène HUBER-YAHI
Université Paris 1 Panthéon-Sorbonne
helene.huber@univ-paris1.fr
Rachid SENOUSSI
INRA PACA
rachid.senoussi@inra.fr
Pascale TUBERT
Inserm
pascale.tubert@inserm.fr
Min-ge XIE
Rutgers University, Rutgers
Etats-Unis
mxie@stat.rutgers.edu