During the last year, articles submitted to the Journal of Social Work Education (JSWE) were not only reviewed through standard channels but, as is the custom of some medical journals (e.g., BMJ), the Editor-in-Chief asked that relevant submissions be statistically reviewed and detailed comments provided to the authors. Through this process, JSWE's statistical reviewers have developed a set of good practice guidelines, which are set forth below. The guidelines fall into three general areas: (1) description of the sample and data, (2) discussion of statistical model choice and test statistics used, and (3) model interpretation and presentation of results. It is the opinion of the statistical reviewers that developing guidelines for good practice in empirical research is more relevant now than ever. The information technology revolution over the last 15 years has made available to researchers huge and complex administrative databases and an ever-growing arsenal of computer-intensive statistical procedures. Although these tools and data are becoming widely available and easy to use, it is critical to understand both the content of the data and the capability and limitations of the statistical tools employed in order to maintain the quality of social work research.
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About the Author: Aron Shlonsky is doctoral candidate, School of Social Welfare, Amy D'Andrade is doctoral student, School of Social Welfare, and M. Alan Brookhart is a doctoral student, Division of Biostatistics, School of Public Health, University of California, Berkeley. All authors are research associates at the Center for Social Services Research, University of California, Berkeley.