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On Using Bayesian Methods to Address Small Sample Problems

Structural equation modeling, 2016-09, Vol.23 (5), p.750-773

McNeish, Daniel

2016

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Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences

Multivariate behavioral research, 2015-09, Vol.50 (5), p.471-484

McNeish, Daniel M.

2015

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Fixed Effects Models Versus Mixed Effects Models for Clustered Data: Reviewing the Approaches, Disentangling the Differences, and Making Recommendations

Psychological methods, 2019-02, Vol.24 (1), p.20-35

2019

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The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

Educational psychology review, 2016-06, Vol.28 (2), p.295-314

2016

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Differentiating between mixed-effects and latent-curve approaches to growth modeling

Behavior research methods, 2018-08, Vol.50 (4), p.1398-1414

2018

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Modeling Sparsely Clustered Data: Design-Based, Model-Based, and Single-Level Methods

Psychological methods, 2014-12, Vol.19 (4), p.552-563

2014

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Thanks Coefficient Alpha, We'll Take It From Here

Psychological methods, 2018-09, Vol.23 (3), p.412-433

2018

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The Thorny Relation Between Measurement Quality and Fit Index Cutoffs in Latent Variable Models

Journal of personality assessment, 2018-01, Vol.100 (1), p.43-52

2018

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Bayesian Versus Frequentist Estimation for Structural Equation Models in Small Sample Contexts: A Systematic Review

Structural equation modeling, 2020-01, Vol.27 (1), p.131-161

2020

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Using Data-Dependent Priors to Mitigate Small Sample Bias in Latent Growth Models: A Discussion and Illustration Using Mplus

Journal of educational and behavioral statistics, 2016-02, Vol.41 (1), p.27-56

McNeish, Daniel M.

2016

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Multilevel and Single-Level Models for Measured and Latent Variables When Data Are Clustered

Educational psychologist, 2016-10, Vol.51 (3-4), p.317-330

2016

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The Role of Measurement Quality on Practical Guidelines for Assessing Measurement and Structural Invariance

Educational and psychological measurement, 2016-08, Vol.76 (4), p.533-561

2016

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Specifying Location-Scale Models for Heterogeneous Variances as Multilevel SEMs

Organizational research methods, 2021-07, Vol.24 (3), p.630-653

McNeish, Daniel

2021

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Small Sample Methods for Multilevel Modeling: A Colloquial Elucidation of REML and the Kenward-Roger Correction

Multivariate behavioral research, 2017-09, Vol.52 (5), p.661-670

McNeish, Daniel

2017

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Using Phantom Variables in Structural Equation Modeling to Assess Model Sensitivity to External Misspecification

Psychological methods, 2017-12, Vol.22 (4), p.616-631

2017

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Exploratory Factor Analysis With Small Samples and Missing Data

Journal of personality assessment, 2017-11, Vol.99 (6), p.637-652

McNeish, Daniel

2017

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Clustered data with small sample sizes: Comparing the performance of model-based and design-based approaches

Communications in statistics. Simulation and computation, 2017-02, Vol.46 (2), p.855-869

2017

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Dynamic Fit Index Cutoffs for Categorical Factor Analysis With Likert-Type, Ordinal, or Binary Responses

The American psychologist, 2023-12, Vol.78 (9), p.1061-1075

2023

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Award for Distinguished Scientific Early Career Contributions to Psychology: Daniel McNeish

The American psychologist, 2023-12, Vol.78 (9), p.1058-1060

Cooper, Harris

2023

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Missing data methods for arbitrary missingness with small samples

Journal of applied statistics, 2017-01, Vol.44 (1), p.24-39

McNeish, Daniel

2017

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Psychometric properties of sum scores and factor scores differ even when their correlation is 0.98: A response to Widaman and Revelle

Behavior research methods, 2023-12, Vol.55 (8), p.4269-4290

McNeish, Daniel

2023

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Dynamic Measurement Modeling: Using Nonlinear Growth Models to Estimate Student Learning Capacity

Educational researcher, 2017-08, Vol.46 (6), p.284-292

2017

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A practical guide to selecting and blending approaches for clustered data: Clustered errors, multilevel models, and fixed-effect models

Psychological methods, 2023-11

McNeish, Daniel

2023

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Thinking twice about sum scores

Behavior research methods, 2020-12, Vol.52 (6), p.2287-2305

2020

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Multilevel Mediation With Small Samples: A Cautionary Note on the Multilevel Structural Equation Modeling Framework

Structural equation modeling, 2017-07, Vol.24 (4), p.609-625

McNeish, Daniel

2017

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On Using Bayesian Methods to Address Small Sample Problems

Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences

Fixed Effects Models Versus Mixed Effects Models for Clustered Data: Reviewing the Approaches, Disentangling the Differences, and Making Recommendations

The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

Differentiating between mixed-effects and latent-curve approaches to growth modeling

Modeling Sparsely Clustered Data: Design-Based, Model-Based, and Single-Level Methods

Thanks Coefficient Alpha, We'll Take It From Here

The Thorny Relation Between Measurement Quality and Fit Index Cutoffs in Latent Variable Models

Bayesian Versus Frequentist Estimation for Structural Equation Models in Small Sample Contexts: A Systematic Review

Using Data-Dependent Priors to Mitigate Small Sample Bias in Latent Growth Models: A Discussion and Illustration Using Mplus

Multilevel and Single-Level Models for Measured and Latent Variables When Data Are Clustered

The Role of Measurement Quality on Practical Guidelines for Assessing Measurement and Structural Invariance

Specifying Location-Scale Models for Heterogeneous Variances as Multilevel SEMs

Small Sample Methods for Multilevel Modeling: A Colloquial Elucidation of REML and the Kenward-Roger Correction

Using Phantom Variables in Structural Equation Modeling to Assess Model Sensitivity to External Misspecification

Exploratory Factor Analysis With Small Samples and Missing Data

Clustered data with small sample sizes: Comparing the performance of model-based and design-based approaches

Dynamic Fit Index Cutoffs for Categorical Factor Analysis With Likert-Type, Ordinal, or Binary Responses

Award for Distinguished Scientific Early Career Contributions to Psychology: Daniel McNeish

Missing data methods for arbitrary missingness with small samples

Psychometric properties of sum scores and factor scores differ even when their correlation is 0.98: A response to Widaman and Revelle

Dynamic Measurement Modeling: Using Nonlinear Growth Models to Estimate Student Learning Capacity

A practical guide to selecting and blending approaches for clustered data: Clustered errors, multilevel models, and fixed-effect models

Thinking twice about sum scores

Multilevel Mediation With Small Samples: A Cautionary Note on the Multilevel Structural Equation Modeling Framework

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