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Teacher’s Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation

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Version 2 2022-11-16, 19:40
Version 1 2022-03-25, 20:40
journal contribution
posted on 2022-03-25, 20:40 authored by Eric S. Kruger, Davood Tofighi, Yu-Yu Hsiao, David P. MacKinnon, M. Lee Van Horn, Katie Witkiewitz

Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.


This work was supported by NIAAA R01 [grant number AA025539 to Katie Witkiewitz and Davood Tofighi: MPIs] and NIDA [grant number R37DA09757 to David P. MacKinnon: PI].