Helms, Henze, Sass, and Mifsud (2006) defined good practices for internal consistency reporting, interpretation, and analysis consistent with an alpha-as-data perspective. Their viewpoint (a) expands on previous arguments that reliability coefficients are group-level summary statistics of samples' responses rather than stable properties of scales or measures and (b) encourages researchers to investigate characteristics of reliability data for their own samples and subgroups within their samples. In Study 1, we reviewed past and current reliability reporting practices in a sample of Psychological Assessment articles published across 3 decades (i.e., from the years 1989, 1996, and 2006). Results suggested that contemporary and past researchers' reliability reporting practices have not improved over time and generally were not consistent with good practices. In Study 2, we analyzed an archival data set to illustrate the real-life repercussions of researchers' ongoing misconstrual and misuse of reliability data. Our analyses suggested that researchers should conduct preliminary analyses of their data to determine whether their data fit the assumptions of their reliability analyses. Also, the results indicated that reliability coefficients varied across racial or ethnic and gender subgroups, and these variations had implications for whether the same depression measure should be used across groups. We concluded that the alpha-as-data perspective has implications for one's choice of psychological measures and interpretation of results, which subsequently affect conclusions and recommendations. We encourage researchers to recognize the people behind their data by adopting better practices in internal consistency reporting, analysis, and interpretation.

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