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We argue that: (1) whether articles contain numeric data should be irrelevant to the evaluation process; (2) the desirability of numeric real, numeric synthetic, or nonnumeric data depends on the research objective; (3) assumptions can and should sometimes substitute for additional data; and (4) equal scrutiny should be given to data collection procedures, regardless of whether the researcher influences the collection or not. Finally, rather than focusing on data, evaluation of research should focus on whether the research provides compelling evidence for the conclusions.