@article{94913f0a6f39428fbebac8e15bf9d7f1,
title = "Teacher{\textquoteright}s Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation",
abstract = "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.",
keywords = "Behavior change, confounding, latent growth curve mediation modeling, mediation, sensitivity analyses",
author = "Kruger, {Eric S.} and Davood Tofighi and Hsiao, {Yu Yu} and MacKinnon, {David P.} and {Lee Van Horn}, M. and Katie Witkiewitz",
note = "Funding Information: We would like to thank local agronomists and extension agents in each country for their help in data collection. We acknowledge the Swiss Agency for Development and Cooperation for financial support to conduct the CORIGAP survey (Grant 681 number 7F-08412.02 to A.M.S.) and also the Bill and Melinda Gates Foundation for their support through the CGIAR Excellence in Agronomy 2030 Incubation Phase (Grant number INV-005431 to P.G.). We also thank the China Postdoctoral Science Foundation (2020M682439 to S.Y.), the China Scholarship Council (201706760015 to S.Y.), the Belt and Road Center for Sustainable Rice Production, the Indonesian Agency for Agricultural Research and Development (IAARD), the Office of Global Engagement at the Institute of Agriculture and Natural Resources (IANR) at the University of Nebraska-Lincoln (UNL) and the UNL Daugherty Water for Food Global Institute. Publisher Copyright: {\textcopyright} 2022 Taylor & Francis Group, LLC.",
year = "2022",
doi = "10.1080/10705511.2022.2045203",
language = "English (US)",
journal = "Structural Equation Modeling",
issn = "1070-5511",
publisher = "Psychology Press Ltd",
}