Difference-in-Differences as an Alternative to Pretest–Posttest Regression for Social Work Intervention Evaluation and Research.

ANALYSIS of covariance; DECISION making; EXPERIMENTAL design; REGRESSION analysis; STATISTICAL sampling; SCHOOL children; SOCIAL work research; MATHEMATICAL variables; PRE-tests & post-tests; DESCRIPTIVE statistics

Nonrandomized evaluation designs are an important part of social work research because randomization is not always feasible in social work settings. Although randomly assigned groups are assumed to be equivalent, nonrandomly assigned groups are not. In nonrandomized settings, designs with multiple waves are ideal, but two-wave designs are still widely used. A common method for estimating a treatment effect in nonrandom two-wave designs is the pretest–posttest model. However, depending on relationships among participants and the method of assignment to treatment groups, researchers should consider a difference-in-differences approach to testing treatment effects. Authors describe and compare the pretest–posttest and difference-in-differences approaches and assumptions and offer guidelines, developed from a literature review, about the conditions under which each model is likely to be best. Authors also demonstrate the decision-making process and application of the methods in an evaluation of an elementary school intervention program. [ABSTRACT FROM AUTHOR]

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