Supplemental material
Structural Equation Modeling: A Multidisciplinary Journal
Volume 26, 2019 - Issue 1
Original Articles
Sensitivity Analysis of the No-Omitted Confounder Assumption in Latent Growth Curve Mediation Models
Davood TofighiUniversity of New MexicoCorrespondence[email protected]
http://orcid.org/0000-0001-8523-7776View further author information
http://orcid.org/0000-0001-8523-7776View further author information, , , , & Related Research Data
Causes, Consequences, and Strategies
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SAGE Publications
Is a Heywood Case a Symptom of Misspecification?
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SAGE Publications
The Shape of Correlation Matrices
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JSTOR
Multilevel Analysis : Techniques and Applications, Second Edition
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Springer Berlin Heidelberg
Sensitivity Analysis of the No-Omitted Confounder Assumption in Latent Growth Curve Mediation Models
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Figshare
The insidious effects of failing to include design-driven correlated residuals in latent-variable covariance structure analysis.
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American Psychological Association (APA)
Estimating causal effects of treatments in randomized and nonrandomized studies.
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American Psychological Association
Abusive supervision climate: : A multiple-mediation model of its impact on group outcomes
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Academy of Management
What determines forgiveness in close relationships? The role of post-transgression trust
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Wiley-Blackwell
Structural Equation Modeling: Latent Growth Curve Analysis
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The Shape of Correlation Matrices
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JSTOR
Statistical Approaches for Enhancing Causal Interpretation of the M to Y Relation in Mediation Analysis
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Confounding in statistical mediation analysis: What it is and how to address it.
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American Psychological Association (APA)
Estimating Mediation in Treatment Evaluations
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SAGE Publications
Causal mediation analysis for longitudinal data with exogenous exposure
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Oxford University Press (OUP)
Mediation models for longitudinal data in developmental research.
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Informa UK Limited
Socioeconomic position, health behaviors, and C-reactive protein: A moderated-mediation analysis.
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American Psychological Association (APA)
Identifiability and Exchangeability for Direct and Indirect Effects
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Ovid Technologies (Wolters Kluwer Health)
Using phantom variables in structural equation modeling to assess model sensitivity to external misspecification.
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American Psychological Association (APA)
Applied Longitudinal Data Analysis
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Oxford University Press
Identification, Inference and Sensitivity Analysis for Causal Mediation Effects
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Institute of Mathematical Statistics
Interpretation and identification of causal mediation.
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American Psychological Association (APA)
Bayesian Inference for Causal Effects: The Role of Randomization
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Institute of Mathematical Statistics
The Effect of Different Forms of Centering in Hierarchical Linear Models
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Informa UK Limited
Parameterizing Inequality Constraints on Unique Variances in Linear Structural Models.
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Springer Science and Business Media LLC
Multilevel mediation analysis: The effects of omitted variables in the 1-1-1 model
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Wiley-Blackwell
A Unified Approach
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John Wiley & Sons, Ltd
Estimation of Indirect Effects in the Presence of Unmeasured Confounding for the Mediator–Outcome Relationship in a Multilevel 2-1-1 Mediation Model
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American Educational Research Association (AERA)
Have Multilevel Models Been Structural Equation Models All Along?
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Informa UK Limited
Sensitivity Analysis of the No-Omitted Confounder Assumption in Latent Growth Curve Mediation Models
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Taylor & Francis
Abusive supervision and employees' job performance: A multiple mediation model
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Scientific Journal Publishers Ltd
A general approach to causal mediation analysis.
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American Psychological Association (APA)
Empirical Identification, Heywood Cases, and Related Problems
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SAGE Publications
Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments
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Cambridge University Press (CUP)
An introduction to modern missing data analyses
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Elsevier BV
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