Accessibility navigation

Modeling reciprocal effects in medical research: critical discussion on the current practices and potential alternative models

Usami, S., Todo, N. and Murayama, K. (2019) Modeling reciprocal effects in medical research: critical discussion on the current practices and potential alternative models. PLoS ONE, 14 (9). e0209133. ISSN 1932-6203

Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

[img] Text - Accepted Version
· Restricted to Repository staff only


It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1371/journal.pone.0209133


Longitudinal designs provide a strong inferential basis for uncovering reciprocal effects or causality between variables. For this analytic purpose, a cross-lagged panel model (CLPM) has been widely used in medical research, but the use of the CLPM has recently been criticized in methodological literature because parameter estimates in the CLPM conflate between-person and within-person processes. The aim of this study is to present some alternative models of the CLPM that can be used to examine reciprocal effects, and to illustrate potential consequences of ignoring the issue. A literature search, case studies, and simulation studies are used for this purpose. We examined more than 300 medical papers published since 2009 that applied cross-lagged longitudinal models, finding that in all studies only a single model (typically the CLPM) was performed and potential alternative models were not considered to test reciprocal effects. In 49% of the studies, only two time points were used, which makes it impossible to test alternative models. Case studies and simulation studies showed that the CLPM and alternative models often produce different (or even inconsistent) parameter estimates for reciprocal effects, suggesting that research that relies only on the CLPM may draw erroneous conclusions about the presence, predominance, and sign of reciprocal effects. Simulation studies also showed that alternative models are sometimes susceptible to improper solutions, even when reseachers do not misspecify the model.

Item Type:Article
Divisions:Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology
ID Code:85571
Publisher:Public Library of Science


Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation