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Mega-Meta with covSTATIS: or How to Perform Multivariate Factor Meta-Analysis

Herve Abdi - University of Texas at Dallas
Tuesday May 3, 12-1pm
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Abstract: Traditional meta-analysis procedures were developed to integrate and evaluate multiple studies involving a small number of variables but current scientific practices systematically involve multiple variables often analyzed by multivariate factorial methods such as principal component analysis and its numerous variations. These methods typically generate maps that represent observations and variables as points or vectors in small dimensional spaces: a format that standard meta-analytic procedure cannot easily handle. Here, in order to meta-analyze a set of multivariate studies using the same variables (and/or same observations) we propose to use a multi-table 3-way extension of metric multidimensional scaling (called diSTATIS or covSTATIS) that can integrate the factorial information produced by a set of studies. covSTATIS produces two set of maps: The first set reveals the similarity between the studies and the second set optimally analyzes the common and specific information of the variables in the studies. This approach is illustrated with a meta-analysis of a set of studies using the Survey of Autobiographical Memory (SAM)鈥攁 questionnaire that assesses self-reported remote mnemonic capacities comprising twenty-six variables organized in four subscales.