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Two-Level factor analysis of morphometric characters of honeybees population sampled (Apis mellifera L.) in Turkey
(2009) Kekeçoğlu, M.; Şimşek, G. G.; Soysal, M.I; Gürcan, E.K.
Classical factor analysis assumes that sampling is independent observations. In morphometric researches, however, the data belonged to honeybee usually have hierarchical structure in which individuals are grouped within colonies within different localities and regions. The assumption of independence among observations is not realistic, because sampling units not share common environment, experiences and interactions. Multilevel factor analysis model is an appropriate methodological tool which has been proposed as an extension to confirmatory factor analysis models for analyzing data with hierarchical structure. In this study, we provide a didactic step-by-step guide to exploratory multilevel factor analysis of morphometric characters of honeybees. The results illustrated that the within and between level factor structure of morphometric characters conformed to expectation which is factor solution with three factors of wing, leg and vacular.