James Uanhoro

Bio

I am an assistant professor in the Research Methodology, Measurement, and Statistics program within the Department of Educational Psychology at the University of North Texas. I have a background in Information Systems, and in my downtime, I enjoy using my computing skills to develop statistical tools for applied researchers.

I am a member of and the UNT lead investigator for OMNI-ADRD (https://omni-adrd.org/, NIH grant: 1U24AG092760-01), a network of scientists working to transform how cognitive change is measured and understood by building open, scalable tools that accelerate dementia prevention research and advance brain health for all.

Research interests:

Applied Bayesian data analysis
Multilevel, psychometric, and covariance structure models and their interconnections
Communicating statistical findings & effect sizes
Statistical software development
Single-case research designs

Education:

PhD Educational Studies, Ohio State University (2021)
MS Information Systems, National Tsing Hua University (2016)
BS Information Systems, American University of Nigeria (2012)

I am also a member of Texas State Employees Union (Communication Workers of America, Local 6186), a union for everyone who works for the state of Texas, and the UNT Chapter of AAUP/AFT, a union and professional organisation for academic staff.

Email: james.uanhoro@unt.edu

Teaching

I usually teach regression (fall), structural equation modeling (spring), and simulation (some Falls). And I should teach an applied Bayesian course in the near future.

Additional links

Blog

2024/11/08 The limitations of small variance priors lie in their implementation
2024/04/14 Hierarchical ordinal regression for analysis of single subject data OR Bayesian estimation of overlap and other effect sizes
2023/05/04 AERA 2023 Presentation: Modeling misspecification as a parameter in Bayesian SEMs
2023/04/02 The minorbsem package in R
2022/12/14 Hierarchical Covariance Estimation Approach to Meta-Analytic Structural Equation Modeling
2021/01/18 Traditional SEM overly focuses on LISREL equations to the detriment of dealing with measurement error
2019/11/25 Problems with using odds ratios as effect sizes in binary logistic regression and alternative approaches
2019/09/26 How do you communicate the evidence for the practical significance of an intervention using Bayesian methods?
2019/08/02 When data are not so informative, it pays to choose the sum score over the factor score
2018/11/28 Multidimensional CFA with RStan
2018/10/20 Possibility of heteroskedasticity is a good reason not to dichotomize a continuous variable for use as outcome in logistic regression.
2018/10/07 Should you perform logistic regression on a dichotomized continuous variable when you have access to the continuous variable? I’m not sure.
2018/10/06 Two group mean and variance comparisons
2018/05/07 Modeling the error variance to account for heteroskedasticity
2018/05/07 Simulating data from regression models
2018/02/12 Using binary regression software to model ordinal data as a multivariate GLM
2018/01/02 Using glmer() to perform Rasch analysis
2017/11/16 A Chi-Square test of close fit in covariance-based SEM
2017/10/28 Misspecification and fit indices in covariance-based SEM
2017/09/21 Little’s MCAR test at different sample sizes
2017/09/21 Theil-Sen regression in R
2017/09/19 Linear regression with violation of heteroskedasticity with small samples
2017/08/11 On the interpretation of regression coefficients