Nnamdi Ezike
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
Also affiliated: Troy University (2023); University of Southern Mississippi (2023); Clemson University (2023); Western Kentucky University (2023)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Nnamdi Ezike's research examines the application of statistical modeling and data analysis techniques to diverse fields, including public health, behavioral science, and education. His work has investigated factors influencing marketing of e-cigarette products on Twitter, utilizing infodemiology and time series analysis. Ezike has also explored sentiment analysis of public discourse on tobacco regulations, employing mixed methods approaches. In the realm of child development, his research has analyzed early intervention programs for young children with Autism Spectrum Disorder, drawing on his collaborators' expertise from the University of Arkansas for Medical Sciences, University of Arkansas at Fayetteville, and University of Arkansas at Little Rock. His methodological contributions include simulations to evaluate statistical models, such as path analysis with nonnormal continuous data and Bayesian model selection.
Metrics
- h-index: 5
- Publications: 12
- Citations: 35
Selected Publications
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Pledging Engagement: Motivations and Intentions for College Sport Attendance among Greek-Letter Organizations (2023)
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Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis (Preprint) (2023)
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Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis (2023)
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Model-data fit evaluation: posterior checks and Bayesian model selection (2022)
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Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (2022)
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Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint) (2022)
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Analysis of a Statewide Early Intervention Program for Young Children with ASD (2021)
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Monte Carlo Simulation in Item Response Theory Applications Using SAS (2020)
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Employment supports in early work experiences for transition-age youth with disabilities who receive Supplemental Security Income (SSI) (2019)
Collaboration Network
Top Collaborators
- Analysis of a Statewide Early Intervention Program for Young Children with ASD
- Model-data fit evaluation: posterior checks and Bayesian model selection
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
Showing 5 of 6 shared publications
- Analysis of a Statewide Early Intervention Program for Young Children with ASD
- Model-data fit evaluation: posterior checks and Bayesian model selection
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis (Preprint)
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis (Preprint)
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis (Preprint)
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis
- Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis (Preprint)
- Analysis of a Statewide Early Intervention Program for Young Children with ASD
- Analysis of a Statewide Early Intervention Program for Young Children with ASD
- Analysis of a Statewide Early Intervention Program for Young Children with ASD
- Analysis of a Statewide Early Intervention Program for Young Children with ASD
- Pledging Engagement: Motivations and Intentions for College Sport Attendance among Greek-Letter Organizations
- Pledging Engagement: Motivations and Intentions for College Sport Attendance among Greek-Letter Organizations
- Pledging Engagement: Motivations and Intentions for College Sport Attendance among Greek-Letter Organizations
- Pledging Engagement: Motivations and Intentions for College Sport Attendance among Greek-Letter Organizations
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