James Uanhoro

Bio

I am a fifth-year doctoral candidate within the Quantitative Research, Evaluation and Measurement program in the Educational Studies department at Ohio State University. My advisor is Professor Ann O’Connell. I have a background in Information Systems, and in my downtime, I enjoy using my computing skills to develop statistical tools for applied researchers. For my dissertation, I am using the connection between SEM and regression to develop SEM models for non-Gaussian data; the estimation method is Bayesian. My interests are causal inference, applied Bayesian modeling, communicating statistical findings, statistics education, API development.

I will be joining the faculty in the Research, Measurement & Statistics program (Educational Psychology) at the University of North Texas as an Assistant Professor in Fall 2021.

Email: uanhoro.1@osu.edu

Teaching

I am a graduate associate at the Center on Education and Training for Employment within the College of Education and Human Ecology.

Lab instruction history:

ESQREM 7651: Regression Analysis (2 years)
ESQREM 6641: Introduction to Educational Statistics (1 year)

Blog

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