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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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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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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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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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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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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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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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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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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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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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Thinking twice about sum scores

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

2020

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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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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

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

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

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

Exploratory Factor Analysis With Small Samples and Missing Data

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

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

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

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

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

Thinking twice about sum scores

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

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

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