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Journal of Personality Assessment|December 9, 2016
Exploratory Factor Analysis With Small Samples and Missing DataDaniel McNeishMultivariate Behavioral Research|December 3, 2016
Nonlinear Growth Models as Measurement Models: A Second-Order Growth Curve Model for Measuring PotentialDaniel McNeish, Denis DumasBehavior Research Methods|September 13, 2019
Covariance pattern mixture models: Eliminating random effects to improve convergence and performanceDaniel McNeish, Jeffrey HarringBehavior Research Methods|February 10, 2025
Reliability representativeness: How well does coefficient alpha summarize reliability across the score distribution?Daniel McNeish, Denis DumasPsychological Methods|June 5, 2018
Fixed effects models versus mixed effects models for clustered data: Reviewing the approaches, disentangling the differences, and making recommendationsDaniel McNeish, Ken KelleyPsychological Methods|August 7, 2025
Exploring how many categories are needed to model ordinal intensive longitudinal data as continuous with dynamic structural equation modelsDaniel McNeish, Andrea SavordPsychological Methods|December 23, 2021
Perspectives on Bayesian inference and their implications for data analysisRoy Levy, Daniel McNeishBehavior Research Methods|October 26, 2017
Differentiating between mixed-effects and latent-curve approaches to growth modelingDaniel McNeish, Tyler MattaMultivariate Behavioral Research|December 25, 2016
Accommodating Small Sample Sizes in Three-Level Models When the Third Level is IncidentalDaniel McNeish, Kathryn R WentzelStatistical Methods in Medical Research|January 13, 2021
Improving convergence in growth mixture models without covariance structure constraintsDaniel McNeish, Jeffrey R HarringPageof 44