Multiple abstract variance analysis (original) (raw)

Multiple abstract variance analysis (MAVA), is a statistical technique used to estimate the proportion of variance in a phenotypic trait due to genetic and environmental factors. It was developed by psychologist Raymond B. Cattell in order to enable the analysis of data from multiple independent sources to estimate the causes of trait variation. Cattell originally described the technique in a 1960 paper. MAVA aims to estimate the relative genetic and environmental contributions to trait variation by comparing variances between families to those within families on the trait under study. As such, it is considered a "more systematic and comprehensive approach" than the classical correlation method of heritability estimation. MAVA later formed the basis of Cattell's 16PF Questionnaire.