đź‘Ź Hello!
I'm Jingwei Gao, a first-year PhD student in the Department of Media and Comm at City University of Hong Kong, under the supervision of Prof. ZHU Jian Hua Jonathan.
Before starting my PhD, I earned a Master's degree in Communication from Peking University HSBC Business School in 2021, where I was advised by Dr. Weiming Ye. After that, I worked as a Product Designer at Tencent Financial Technology for one year.
Check my Curriculum Vitae for more info.
🌟Featured
Method | Structural Equation Models
Posted on:December 27, 2023SEM is an umbrella term referring to a framework of linear models designed to explore relationships among both observable and unobservable variables.
Method | Linear Mixed Models
Posted on:December 12, 2023A Linear Mixed Model is a statistical model that is particularly useful for analyzing data that have both fixed and random effects, which are pretty common in fields like psychology.
Method | Regression Analysis
Posted on:April 30, 2023A comprehensive guide to regression analysis covering both continuous and discrete data, tailored for social science students involved in quantitative research.
Method | Network Analysis
Posted on:April 16, 2023An introduction to social network analysis, spanning analysis techniques from individual nodes to group dynamics, incorporating descriptive and inferential methodologies.
📆Recent Posts
Statistics | Endogeneity
Posted on:March 5, 2025Cov(x,u)≠0
Statistics | Proportional-odds Logistic Regression
Posted on:February 27, 2025Ordered logistic regression with proportional odds assumption.
Statistics | Regression Diagnostics
Posted on:February 22, 2025You cannot simply walk away after running a regression. There are guidelines for diagnosing both linear and logistic regression models.
Statistics | Poisson Model
Posted on:January 16, 2025The Poisson distribution is often used to count the number of “successes” in scenarios involving a large number of trials, each with a small probability of success.
Statistics | The Bootstrap
Posted on:January 10, 2025Bootstrap is a powerful statistical tool used to quantify the uncertainty associated with a given statistic or estimator.