Walter Leite

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University of Florida

United States

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About

Walter Leite is a Professor at the University of Florida, United States. His research primarily focuses on educational measurement and statistics, with recent articles examining the impacts of sample sizes in randomized trials, methods for addressing social desirability bias, and applications of AI in predicting student learning outcomes. Additionally, he explores innovative statistical techniques such as propensity score matching and item response theory.

Recent Grants

Grant: Close

Efficacy of Prime Online: Teacher Professional Development for Inclusive Elementary Mathematics Classrooms

Open Date: 2018-08-15

Close Date: 2022-08-14

Grant: Close

BEST in CLASS-Web: A Web-Based Intervention Supporting Early Childhood Teachers' Use of Evidence-Based Practices with Young Children at Risk for Emotional/Behavioral Disorders

Open Date: 2016-08-01

Close Date: 2019-07-31

Grant: Close

Precision Education: The Virtual Learning Lab

Open Date: 2016-07-01

Close Date: 2021-06-30

Grant: Close

Postdoctoral Research Training Fellowships in Early Intervention and Early Learning in Special Education at the University of Florida

Open Date: 2012-05-15

Close Date: 2015-05-14

Grant: Close

Postdoctoral Research Training Fellowships in Early Intervention and Early Learning in Special Education at the University of Florida

Open Date: 2012-05-15

Close Date: 2015-05-14

Articles (19)

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UNITED STATES

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Anne Corinne Huggins

University of Florida

UNITED STATES

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Huan KUANG

Assistant Professor

Florida State University

UNITED STATES

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Katerina M. Marcoulides

University of Minnesota

UNITED STATES

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M. David Miller

Professor and Director

University of Florida

UNITED STATES

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Anne Mathews

UNITED STATES

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Walter Leite

Research Interests

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Recent Grants

Articles (19)

Evaluating the Performance of a Regularized Differential Item Functioning Method for Testlet-Based Polytomous Items

Using Ant Colony Optimization to Identify Optimal Sample Allocations in Cluster-Randomized Trials

The Impacts of Small Teacher-Level Sample Sizes in Cluster-Randomized Trials

A comparison of random forest-based missing imputation methods for covariates in propensity score analysis.

Enhancing the Detection of Social Desirability Bias Using Machine Learning: A Novel Application of Person-Fit Indices

Using Simulated Annealing to Investigate Sensitivity of SEM to External Model Misspecification

A Comparison of Person-Fit Indices to Detect Social Desirability Bias

Unreliable Continuous Treatment Indicators in Propensity Score Analysis

Examining gender and the longitudinal effect of weight conscious drinking dimensions on body mass index among a college freshman cohort

Propensity Score Matching with Cross-Classified Data Structures: A Comparison of Methods

A comparison between the piecewise and parallel-process piecewise latent growth models

Comparison of Propensity Score Weighting Methods to Remove Selection Bias in Average Treatment Effect Estimates

Estimating propensity scores using neural networks and traditional methods: a comparative simulation study

Using fair AI to predict students’ math learning outcomes in an online platform

Teacher strategies to use virtual learning environments to facilitate algebra learning during school closures

The relationship between self-regulated student use of a virtual learning environment for algebra and student achievement: An examination of the role of teacher orchestration

Model Specification Searches in Structural Equation Modeling with a Hybrid Ant Colony Optimization Algorithm

Assessing Ability Recovery of the Sequential IRT Model With Unstructured Multiple-Attempt Data

A Tutorial on Artificial Neural Networks in Propensity Score Analysis

Collaborators (11)

Albert Ritzhaupt

Chenglu Li

Sarah Colby

Zuchao Shen

Wenjun Zhou

Wanli Xing

Anne Corinne Huggins

Huan KUANG

Katerina M. Marcoulides

M. David Miller

Anne Mathews

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