A Nested Analysis for Data Collected from Groups

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Abstract
Traditionally, most crowding research involves the observation of subjects in groups formed either by manipulation in the laboratory or by natural factors in field studies. The conventional analysis of such data employs the group mean (or median) as the experimental unit and results in large numbers of individuals being observed to yield comparatively few degrees of freedom for the statistical tests of treatment effects. This paper examines the difference between dependent and independent responses and suggests that, for the case of independence, a nested analysis of variance model is appropriate. The advantages of this analytic approach are explained, and conditions are discussed under which more powerful test of treatment effects may be obtained.

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