In Search of a Dependent Variable: Comment on Avakame
In a previous Criminology article, Avakame (1998) applies hierarchical linear modeling (HLM) techniques to Supplementary Homicide Reports (SHR) to disentangle individual- and aggregate-level factors associated with offending. A close reading of his analysis reveals serious flaws in the dependent variable, which renders the results meaningless. Although it is ambiguous whether Avakame intended to model homicide “risk” or “frequency,” either is problematic. “Homicide frequency” has no logical connection to the individual-level predictors; “homicide risk” is constant in SHR data, which makes the analysis impossible. In detailing these problems, we spell out the logical data requirements and offer sound empirical examples for an HLM analysis.
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