Centers for Research on Prevention Science and Methodology
The Prevention Science and Methodology Group (PSMG) is an interdisciplinary network that has been supported by the National Institute of Mental Health (NIMH) and the National Institute on Drug Abuse (NIDA) for the past 20 years. It brings together prevention scientists conducting cutting-edge randomized trials and expert methodologists who are committed to addressing the key design and analytic problems in prevention research. PSMG has attempted to anticipate needs for methodological development and to have new methods ready when the trials demand them (Albert and Brown, 1990; Brown, Costigan, and Kendziora, 2008).
As the field of prevention science has matured over the past 15 years, PSMG has worked on such problems as generalized estimating equations as a way to account for uncertainty in longitudinal and multilevel inferences (Zeger, Liang, and Albert, 1988; Brown, 1993b); methods to assess intervention impact with growth models (Muthén, 1997, 2007; Muthén, Jo, and Brown, 2003; Muthén and Curran, 1997; Curran and Muthén, 1999; Muthén and Shedden, 1999; Carlin, Wolfe, et al., 2001; Muthén, Brown, et al., 2002; Wang, Brown, and Banderen-Roche, 2005; Muthén and Asparouhov, 2006; Asparouhov and Muthén, 2007); variation in impact by baseline characteristics (Brown, 1993a, 1993b; Ialongo, Werthamer, et al., 1999; Brown, Costigan, and Kendziora, 2008); mediation analysis (MacKinnon, 2008); multilevel models for behavior observations (Dagne, Howe, et al., 2002; Dagne, Brown, and Howe, 2003, 2007; Howe, Dagne, and Brown, 2005; Snyder, Reid, et al., 2006); modeling of self-selection factors (Jo, 2002; Jo and Muthén 2001; Jo, Asparouhov, et al., in press); and randomized trial designs specifically for prevention studies (Brown and Liao, 1999; Brown, Wyman, et al., 2006; Brown,
Prevention methodology, or the use of statistical methodology and statistical computing, is a core discipline in the field of prevention science (Eddy, Smith, et al., 2005) and is one of the new interdisciplinary fields embodied in the NIH Roadmap.1 It aims to invent new techniques or apply existing ones to address the fundamental questions that prevention science seeks to answer and to develop ways to present these findings not only to the scientific community but also to policy makers, to advocates and community and institutional leaders, and to families, the ultimate potential beneficiaries of prevention programs and often, their potential consumers.
Methodologists make inferences about program effects by relying on three things: (1) measures of key constructs, such as risk and protective factors or processes, symptoms, disorders, or other outcomes, and program implementation, fidelity, or participation; (2) a study design that