ArticleStructural equation modeling : a multidisciplinary journal2019
Sensitivity Analysis of the No-Omitted Confounder Assumption in Latent Growth Curve Mediation Models.
Article in Structural equation modeling : a multidisciplinary journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Synthesis of single-case design mediation effects using two-stage multilevel modeling.Behavior research methods · 2026Article
- Gendered racial microaggressions, self-silencing, and disordered eating in Black women.Body image · 2025Article
- Public health spending in Sub-Saharan Africa: exploring transmission mechanisms using the latent growth curve mediation model.Health economics review · 2024Article
- The impact of omitting confounders in parallel process latent growth curve mediation models: Three sensitivity analysis approaches.Structural equation modeling : a multidisciplinary journal · 2024Article
- Mechanisms of Behavior Change in Substance Use Disorder With and Without Formal Treatment.Annual review of clinical psychology · 2022Review
- Teacher's Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation.Structural equation modeling : a multidisciplinary journal · 2022Article
- The impact of measurement error and omitting confounders on statistical inference of mediation effects and tools for sensitivity analysis.Psychological methods · 2021Article
- Income disparity in school readiness and the mediating role of perinatal maternal mental health: a longitudinal birth cohort study.Epidemiology and psychiatric sciences · 2021Article
- Sensitivity Analysis in Nonrandomized Longitudinal Mediation Analysis.Frontiers in psychology · 2021Article
- Improved inference in mediation analysis: Introducing the model-based constrained optimization procedure.Psychological methods · 2020Article
- The (Lack of) Replication of Self-Reported Mindfulness as a Mechanism of Change in Mindfulness-Based Relapse Prevention for Substance Use Disorders.Mindfulness · 2019Article
- Bootstrap Model-Based Constrained Optimization Tests of Indirect Effects.Frontiers in psychology · 2019Article
- Indirect Effects in Sequential Mediation Models: Evaluating Methods for Hypothesis Testing and Confidence Interval Formation.Multivariate behavioral researchArticle
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Authors and funding
6 authors.
Funding
Abstract
Latent growth curve mediation models are increasingly used to assess mechanisms of behavior change. For latent growth mediation model, like any another mediation model, even with random treatment assignment, a critical but untestable assumption for valid and unbiased estimates of the indirect effects is that there should be no omitted variable that confounds indirect effects. One way to address this untestable assumption is to conduct sensitivity analysis to assess whether the inference about an indirect effect would change under varying degrees of confounding bias. We developed a sensitivity analysis technique for a latent growth curve mediation model. We compute the biasing effect of confounding on point and confidence interval estimates of the indirect effects in a structural equation modeling framework. We illustrate sensitivity plots to visualize the effects of confounding on each indirect effect and present an empirical example to illustrate the application of the sensitivity analysis.
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