2 citations · 3 across the 7 of their papers we have counts for
7 papers
Racial Comparability in Authoritarianism Scales: Latent Beliefs or Biased Measurement?
Bang Quan Zheng
Racial differences in authoritarianism are widely used to explain variation in political attitudes, yet it is unclear whether they reflect true latent differences or measurement ar…
Identifying Unmeasured Confounders in Panel Causal Models: A Two-Stage LM-Wald Approach
Bang Quan Zheng
Panel data are widely used in political science to draw causal inferences. However, these models often rely on the strong and untested assumption of sequential ignorability--that n…
Rethinking Structural Equation Modeling in Political Science: Challenges, Best Practices, and Future Directions
Bang Quan Zheng
Structural Equation Modeling (SEM) or Covariance Structure Analysis (CSA) is a versatile and powerful method in the social and behavioral sciences, providing a framework for modeli…
Enhancing Model Fit Evaluation in SEM: Practical Tips for Optimizing Chi-Square Tests
Bang Quan Zheng, Peter M. Bentler
This paper underscores the vital role of the chi-square test within political science research utilizing structural equation modeling (SEM). The ongoing debate regarding the inclus…
Group Differences in Opinion Instability and Measurement Errors: A G-Theory Analysis of College Students
Bang Quan Zheng
This study examines opinion instability among individuals from different ethnic groups (White, Latino, and Asian Americans) by analyzing measurement errors in survey measures. Usin…
Improved LM Test for Robust Model Specification Searches in Covariance Structure Analysis
Bang Quan Zheng, Peter M. Bentler
Covariance Structure Analysis (CSA) or Structural Equation Modeling (SEM) is critical for political scientists measuring latent structural relationships, allowing for the simultane…
Efficient estimation of weighted cumulative treatment effects by double/debiased machine learning
Shenbo Xu, Bang Zheng, Bowen Su +5
In empirical studies with time-to-event outcomes, investigators often leverage observational data to conduct causal inference on the effect of exposure when randomized controlled t…