Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free: https://www.ghostery.com/fr/products/

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site: http://www.youronlinechoices.com/fr/controler-ses-cookies/, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Realytics
Google Analytics
Spoteffects
Optimizely

Targeted advertising cookies

DoubleClick
Mediarithmics

The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at cil-dpo@inra.fr or by post at:

INRA
24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal

Home page

Meta-analysis of experimental data : application in animal nutrition

INRA Prod. Anim., 18(1), 63-73.

D. SAUVANT ¹, P. SCHMIDELY ¹, J.J. DAUDIN ²

1INRA INAPG, UMR Physiologie de la Nutrition et Alimentation, n° 791, 16 rue Claude Bernard, 75231 Paris Cedex 05

2 INRA INAPG, ENGREF, Mathématique et Informatique Appliquée, n° 518, 16 rue Claude Bernard, 75231 Paris Cedex 05

Abstract 

Research in animal sciences and in nutrition in particular, requires more and more important treatment of databases. Indeed, for subjectsof interest, the number of publications and of results per publication is largely increasing. It is thus more and more necessary to be ableto extract quantitative data from the literature. As a consequence, the methods of statistical meta-analysis of experimental databases havebecome essential and it is important to adequately implement them. The management of the meta-analysis is done in several phases. Thefirst phase concerns the definition of working objectives and specifications that will be decisive for the choice of the applicant publications.These should be scrupulously evaluated before being integrated into the database. During their integration, it is important to carefullyencode (experiments, treatments, …) which will be important reference points for the rest of the analysis. The databases that havebeen built this way give rise to interpretation difficulties; they contain missing data and do not represent a classical experimental system.It is recommended to include a first step of careful graphical interpretation in order to have a global and a specific view of the data. Thisphase is followed by a study of the meta-system made up of the database to be interpreted. These different steps condition the definitionof the applied statistics model. This should allow to differentiate the variations of inter- and intra-experiments; it can integrate the qualitativeor quantitative factors. It also includes fixed or random effects. Finally, it may also consider systems of weighed data. After theadjustment of the model, it is important to develop a post-analytic study that consists in studying the residual variations and the roles ofthe different treatments and experiments in the results that were obtained. At this stage, it is often necessary to return to one of the earliersteps. This way, the meta-analysis becomes a heuristic step.

Download documents