Data table in which a single set of individuals is described by several groups of variables are frequently encountered. In the factor analysis framework, taking into account different groups of variables in a unique analysis firstly raises the problem of balancing the different group. This problem being solved, beyond classical outputs from factor analysis, it is necessary to have at one’s disposal specific tools in order to compare the structure upon individuals induced by the different groups of variables. That is the aim of Multiple Factor Analysis (MFA), factor analysis devoted to such data table. This paper presents the method, its main properties and an application to sensory data.
Key words: Factor analysis, Principal components analysis, Canonical analysis.