title: [Effect models and meta-analysis].
abstract: The effect models are defined as the simple or complex relation that the risk in the treatment group follows when the risk in the control group varies. The standard statistical methods of meta-analysis are based on simple effect models. The use of these methods could induce inaccurate or erroneous results in more complex situations. In this case, it is necessary to adopt a more appropriate effect model, such as the linear effect model. The properties of this kind of model allow the possibility that a treatment can be beneficial and harmful at the same time, in function of the risk without treatment. From this observation, it is advisable to be careful with the use of simple effect models in meta-analysis which can submerge interesting information in the synthesis.
authors.affiliation: Service de Pharmacologie Clinique, Hôpital Cardiologique, Université Claude Bernard, Lyon, France.
authors.forename: M
authors.initials: M
authors.lastname: Cucherat
authors.forename: J P
authors.initials: JP
authors.lastname: Boissel
mesh_terms: D004358:Drug Therapy / Q000706:statistics & numerical data; D006801:Humans; D016014:Linear Models; D015201:Meta-Analysis as Topic