Alberto Maydeu-Olivares

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University of South Carolina

United States

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Alberto Maydeu-Olivares is a Professor at the University of South Carolina, United States. His research interests include structural equation modeling, reliability assessments, and the development of testing methodologies. He has contributed to the field through several recent articles focusing on model fit indices, factor analysis, and the implications of measurement errors in clinical settings.

Recent Grants

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Standardized Goodness of Fit Assessment and Power Computations in Structural Equation Models

Open Date: 2017-07-01

Close Date: 2020-06-30

Articles (12)

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2020

Collaborators (5)

Dexin Shi

Assistant Professor

University of South Carolina

UNITED STATES

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Goran Pavlov

Assistant Professor

University of Texas at El Paso

UNITED STATES

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Javier Revuelta

Universidad Autónoma de Madrid

SPAIN

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Amanda J. Fairchild

University of South Carolina

UNITED STATES

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Taehun Lee

Korea University

SOUTH KOREA

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Alberto Maydeu-Olivares

Research Interests

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About

Recent Grants

Articles (12)

On a general theoretical framework of reliability

Percentage of variance accounted for in structural equation models: The rediscovery of the goodness of fit index.

Using Mixture Factor Analysis to Counter Faking

Asymptotic is Better than Bollen-Stine Bootstrapping to Assess Model Fit: The Effect of Model Size on the Chi-Square Statistic

Assessing Cutoff Values of SEM Fit Indices: Advantages of the Unbiased SRMR Index and Its Cutoff Criterion Based on Communality

Evaluating SEM Model Fit with Small Degrees of Freedom

Item desirability matching in forced-choice test construction

Assessing the Accuracy of Errors of Measurement. Implications for Assessing Reliable Change in Clinical settings

Chi-square Difference Tests for Comparing Nested Models: An Evaluation with Non-normal Data

Factor Analysis for Nominal (First Choice) Data

Estimating causal effects in linear regression models with observational data: The instrumental variables regression model.

Estimating the Maximum Likelihood Root Mean Square Error of Approximation (RMSEA) with Non-normal Data: A Monte-Carlo Study

Collaborators (5)

Dexin Shi

Goran Pavlov

Javier Revuelta

Amanda J. Fairchild

Taehun Lee

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