Abstract
Models considered in the current special issue represent valuable additions to the statistical toolbox of prevention researchers for many types of research questions and designs. Their appropriate use, however, depends on critical evaluation relative to previously existing techniques. This evaluation includes (a.) model choice involving “right-sizing” of the model relative to the amount and quality of data at hand, (b.) examination of the external validity of identified associations relative to observed or latent subgroups, (c.) confirmation of the reasonableness of the functional form assumed by the model, and (d.) identification of influential or outlying observations which unduly affect model fit or parameter estimates. Models in this issue allow for testing of new types of hypotheses in prevention research, and can constitute counterarguments to existing statistical practice. These models may, however, in turn be the object of critical examination of counterarguments a reasonable skeptic may offer.
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Wood, P.K. New Frontiers in Prevention Research Models: Commentary on the Special Issue. Prev Sci 24, 517–524 (2023). https://doi.org/10.1007/s11121-023-01508-2
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DOI: https://doi.org/10.1007/s11121-023-01508-2