S Bougeard

Publications (4)8.76 Total impact

• Article: Multiblock modelling to assess the overall risk factors for a composite outcome.

  S Bougeard, C Lupo, S Le Bouquin, C Chauvin, E M Qannari
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  ABSTRACT: Research in epidemiology may be concerned with assessing risk factors for complex health issues described by several variables. Moreover, epidemiological data are usually organized in several blocks of variables, consisting of a block of variables to be explained and a large number of explanatory variables organized in meaningful blocks. Usual statistical procedures such as generalized linear models do not allow the explanation of a multivariate outcome, such as a complex disease described by several variables, with a single model. Moreover, it is not easy to take account of the organization of explanatory variables into blocks. Here we propose an innovative method in the multiblock modelling framework, called multiblock redundancy analysis, which is designed to handle most specificities of complex epidemiological data. Overall indices and graphical displays associated with different interpretation levels are proposed. The interest and relevance of multiblock redundancy analysis is illustrated using a dataset pertaining to veterinary epidemiology.
  Epidemiology and Infection 04/2011; 140(2):337-47. · 2.84 Impact Factor
• Article: Risk factors for sanitary condemnation in broiler chickens and their relative impact: application of an original multiblock approach.

  C Lupo, S Bougeard, L Balaine, V Michel, I Petetin, P Colin, S LeBouquin, C Chauvin
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  ABSTRACT: An innovative and well-adapted statistical method, called multiblock redundancy analysis, is proposed for a complex health-event analysis to account for the thematic block organization of variables. The outcome block contained the condemnation rates of 404 broiler chicken flocks, distinguishing infectious and traumatic condemnation categories. Explanatory variables were organized in blocks related to the different production stages (farm structure and routine husbandry practices; on-farm flock history and characteristics; catching, transport and lairage conditions; slaughterhouse and inspection features). The aim was to determine risk factors for both condemnation categories, and the relative impact of the different production stages on the whole condemnation rate. Results showed that significant factors were either specific to one condemnation category or related to both categories, and each of the explanatory blocks was involved in the explanation of infectious and traumatic condemnation rates. On-farm flock information explained 40% of the overall condemnation process whereas the other explanatory blocks had similar relative impacts.
  Epidemiology and Infection 09/2009; 138(3):364-75. · 2.84 Impact Factor
• Source

  Available from: Nicolas Rose

  Article: Bayesian estimation of flock-level sensitivity of detection of Salmonella spp., Enteritidis and Typhimurium according to the sampling procedure in French laying-hen houses.

  A Mahé, S Bougeard, A Huneau-Salaün, S Le Bouquin, I Petetin, S Rouxel, F Lalande, P A Beloeil, N Rose
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  ABSTRACT: A study was carried out to estimate the prevalence of flocks infected by Salmonella spp., S. Enteritidis and S. Typhimurium in 521 French laying-hen farms from October 1st 2004 to September 30th 2005 as part of a European Union-wide baseline study to define targets for Salmonella reduction in member states. The sampling scheme prescribed and financed by the European Commission to detect Salmonella in laying-hen flocks was based on 2 dust-samples and 5 faeces-samples per farm. A latent-class Bayesian approach for correlated tests was used to estimate the sensitivity of detection of reduced sampling schemes corresponding to the 16 combinations of 2 dust- and 5 faeces-samples. For each model the full sampling scheme (7 samples) and the reduced protocol were considered as two correlated tests, the biological principle being identical and the reduced protocol being a subset of the full sampling scheme. As the observed apparent prevalence in cage flocks was higher than in other systems (barns, outdoor, or organic) these two sub-populations were considered separately. Bayesian estimation of posterior medians with 95% probability intervals for true prevalence in cage flocks were 0.34 (0.29; 0.39) and 0.13 (0.10; 0.18) for Salmonella spp. and Salmonella Enteritidis+Typhimurium respectively. In alternative flocks posterior medians with 95% probability intervals for true prevalence were 0.09 (0.06; 0.13) and 0.05 (0.03; 0.08) for Salmonella spp. and Salmonella Enteritidis+Typhimurium, respectively. In cage flocks Bayesian estimation of posterior distributions for sensitivity indicated that at least 5 samples, including 2 dust samples were necessary to attain comparable sensitivity levels to the full sampling scheme. In alternative flocks and for Salmonella spp. 6 samples were required to ensure a comparable sensitivity level to the full sampling scheme. Detection sensitivity was improved by increasing the number of dust samples in cage farms and by increasing the total number of samples whatever their type in alternative farms.
  Preventive Veterinary Medicine 05/2008; 84(1-2):11-26. · 2.05 Impact Factor
• Article: Continuum redundancy-PLS regression: A simple continuum approach

  S. Bougeard, M. Hanafi, E.M. Qannari
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  ABSTRACT: The relationships between two data sets are investigated. The aim is to predict one data set from the other. New formulations of Redundancy Analysis and Partial Least Square Regression (PLS) are discussed, clearly showing the connexions between these two popular methods. Moreover, it is shown that the Redundancy Analysis and PLS regression are the two end points of a continuum approach. Properties related to this continuum approach are discussed, showing how the multicolinearity problem is handled. The interest of the general strategy of analysis is illustrated on the basis of a data set pertaining to epidemiology.
  Computational Statistics & Data Analysis 01/2008; 52(7):3686-3696. · 1.03 Impact Factor