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Six Methods for Latent Moderation Analysis in Marketing Research: A Comparison and Guidelines
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Structural Equations with Latent Variables
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An Introduction to Statistical Learning
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Measurement Models for Marketing Constructs
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Simulating Multivariate Nonnormal Distributions
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Maximum Likelihood Estimation of Latent Interaction Effects with the LMS Method
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Determinants of Standard Errors of MLEs in Confirmatory Factor Analysis
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A Monte Carlo study of the effects of correlated method variance in moderated multiple regression analysis
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Challenges in Nonlinear Structural Equation Modeling
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Structural equation modeling in practice: A review and recommended two-step approach.
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Analysis of multiplicative combination rules when the causal variables are measured with error.
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Estimating the nonlinear and interactive effects of latent variables.
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The Correction for Attenuation Due to Measurement Error: Clarifying Concepts and Creating Confidence Sets.
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Misleading interaction and curvilinear terms.
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Structural Equation Models of Latent Interactions: Evaluation of Alternative Estimation Strategies and Indicator Construction.
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When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions.
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Reversed item bias: An integrative model.
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The choice of product indicators in latent variable interaction models: Post hoc analyses.
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Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
inferredcites →https://doi.org/10.1080/10705511.2010.488999openalex-snapshot
Structural Equation Models of Latent Interactions: Clarification of Orthogonalizing and Double-Mean-Centering Strategies
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MplusAutomation : An R Package for Facilitating Large-Scale Latent Variable Analyses in M plus
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Time-Varying Effect Sizes for Quadratic Growth Models in Multilevel and Latent Growth Modeling
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Bayesian estimation of single and multilevel models with latent variable interactions
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Modeling Measurement Errors of the Exogenous Composites From Congeneric Measures in Interaction Models
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Effects of sample size and nonnormality on the estimation of mediated effects in latent variable models
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A Meta-Analysis of Cronbach's Coefficient Alpha
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Unobserved Heterogeneity as an Alternative Explanation for “Reversal” Effects in Behavioral Research
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Reflection on modern methods: five myths about measurement error in epidemiological research
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Meaningful Mediation Analysis: Plausible Causal Inference and Informative Communication
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Digital Goods Are Valued Less Than Physical Goods
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Maximum Likelihood from Incomplete Data Via the EM Algorithm
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Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality
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Common Factor Score Estimates in Multiple Regression Problems
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Advanced Structural Equation Modeling: Issues and Techniques
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Common Method Bias in Regression Models With Linear, Quadratic, and Interaction Effects
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Improving Our Understanding of Moderation and Mediation in Strategic Management Research
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Design and Analysis of Monte Carlo Experiments: Attacking the Conventional Wisdom
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How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power
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Multicollinearity and Measurement Error in Structural Equation Models: Implications for Theory Testing
inferredcites →https://doi.org/10.1509/jm.14.0244openalex-snapshot
The Chief Marketing Officer Matters!
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Have We Progressed Marketing Knowledge? A Meta-Meta-Analysis of Effect Sizes in Marketing Research
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Negative Consequences of Dichotomizing Continuous Predictor Variables
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lavaan : An R Package for Structural Equation Modeling
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Statistical Power Analysis for the Behavioral Sciences
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R: A Language and Environment for Statistical Computing
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Multicollinearity is a red herring in the search for moderator variables: A guide to interpreting moderated multiple regression models and a critique of Iacobucci, Schneider, Popovich, and Bakamitsos (2016)
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