title: On the Practical Interpretability of Cross-Lagged Panel Models: Rethinking a Developmental Workhorse.
abstract: Reciprocal feedback processes between experience and development are central to contemporary developmental theory. Autoregressive cross-lagged panel (ARCL) models represent a common analytic approach intended to test such dynamics. The authors demonstrate that-despite the ARCL model's intuitive appeal-it typically (a) fails to align with the theoretical processes that it is intended to test and (b) yields estimates that are difficult to interpret meaningfully. Specifically, using a Monte Carlo simulation and two empirical examples concerning the reciprocal relation between spanking and child aggression, it is shown that the cross-lagged estimates derived from the ARCL model reflect a weighted-and typically uninterpretable-amalgam of between- and within-person associations. The authors highlight one readily implemented respecification that better addresses these multiple levels of inference.
authors.affiliation: University of Minnesota.
authors.forename: Daniel
authors.initials: D
authors.lastname: Berry
authors.affiliation: RTI International.
authors.forename: Michael T
authors.initials: MT
authors.lastname: Willoughby
mesh_terms: D000293:Adolescent; D000294:Adolescent Behavior / Q000523:psychology*; D041923:Adolescent Development; D002648:Child; D002652:Child Behavior / Q000523:psychology*; D002657:Child Development; D006801:Humans; D008960:Models, Psychological; D015233:Models, Statistical