I was trained in Statistics at Stanford University (M.S. in Stats, expected 2025) and in Psychology at Sun Yat-sen University (M.S. and B.S. in Psych). Prior to Stanford, I have worked on Bayesian analysis, structural equation modeling, and network analysis with Professors Junhao Pan, Edward Ip, Xinya Liang, and Johnny Zhang.
Research Interests in Psychometrics
Evaluating and improving the generalizability of Structural Equation Models.
Identifying model violations in factor analysis, primarily using the Bayesian Lasso.
Other statistical techniques for psychological and educational research, such as network analysis and item response models.
Contact
lijinzhang [at] stanford [dot] eduGoogle Scholar | GitHub | CV
News
08/2024 I received the Stanford Data Science Fellowship, an honor given to ~15 recipients annually across the campus, which will support my stipend and research for the next two years.08/2024 Our paper “A Technology Acceptance Model to Predict Anesthesiologists’ Clinical Adoption of Virtual Reality.” is accepted by Journal of Clinical Anesthesia.
05/2024 I completed the qualifying paper defense and have advanced to candidacy.
05/2024 Our paper “Heterogeneity of item-treatment interactions masks complexity and generalizability in randomized controlled trials” is accepted by Journal of Research on Educational Effectiveness.
11/2023 Our paper “Testing Informative Hypotheses in Factor Analysis Models using Bayes Factors” is accepted by Psychological Methods.
07/2023 Our paper “Variety and Mainstays of the R Developer Community” is accepted by R Journal.
04/2023 Our paper “Bayesian Regularization in Multiple-Indicators Multiple-Causes Models” is accepted by Psychological Methods.
