期刊
PSYCHOLOGY OF ADDICTIVE BEHAVIORS
卷 36, 期 3, 页码 271-283出版社
EDUCATIONAL PUBLISHING FOUNDATION-AMERICAN PSYCHOLOGICAL ASSOC
DOI: 10.1037/adb0000750
关键词
cross-lagged panel model; random-intercept cross-lagged panel model; latent curve models with structured residuals
This study highlights the interpretational limitations of the CLPM in addiction research and provides examples of alternative models. Alternative models show little evidence of prospective within-person associations, but more evidence for between-person associations and wave-specific within-person relations between constructs.
Public Health Significance Statement A commonly used modeling approach in addiction research, the cross-lagged panel model has significant interpretational limitations. Alternative models that accommodate within- and between-person change are recommended. Objective: Models of addiction often posit bidirectional and dynamic associations between constructs relevant to the etiology and maintenance of addictive behaviors. The cross-lagged panel model (CLPM) is commonly used in addiction research but has been critiqued for not appropriately adjusting for between-person variance. Alternatives to the CLPM have been suggested but remain underutilized. The primary purpose of this article is to highlight interpretational limitations of the CLPM and to provide examples of alternative models. Method: We specified CLPM, Random-Intercept CLPM, and a Latent Curve Model with Structured Residuals using four waves of data from Project MATCH (n = 1,201). We modeled prospective relations among depression symptoms and temptation to drink. Substantive inferences and assumptions across models were compared. Results: The CLPM provided the most evidence of significant cross-lagged paths but the poorest fit to the data compared to other models. Alternative models found little evidence of prospective within-person associations, and more evidence for between-person associations and wave-specific within-person relations between depression symptoms and temptation to drink. Conclusions: This study highlights shortcomings of the CLPM and details alternative models to consider. Addiction researchers should consider alternatives to the CLPM to more optimally delineate relations among constructs across time.
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