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It is an unusual commentary indeed when critics speculate about data analysis, findings, and conclusions, rather than reanalyzing any of our data (publicly available through the National Archive of Criminal Justice Data). l Hoffmann and Johnson (henceforth, HJ) have presented (in an earlier paper in this issue) an entirely different study with entirely different variables and entirely different hierarchical linear models (HLM). Surprisingly, they come up with much of the same conclusions regarding the dominance of individual-level predictors. Their cross-level interaction terms, uninformed by theory, account for negligible portions of explained variance. They present a rather narrow view of multilevel modeling that leaves important questions regarding theory and study design completely unaddressed. A number of omissions and errors further weaken their arguments.

The gist of HJ’s argument is that we ignore cross-level …