Jun Xu is a Full Professor  in the Department of Sociology and the Data Science Program at Ball State University. He has a wide range of scholarly interests, including data/statistical science, health, and social sciences (history, political philosophy, and sociology), broadly defined. His primary research interests include data and statistical science (computational social science, Bayesian statistics, categorical data analysis, causal inference, and machine learning), Asia and Asian America (Asian American politics and health, China),  health (health disparities, healthcare systems and utilization), and welfare systems and political economy. He is also interested in and/or has done research on education (comparative and international education, cultural capital). His professional goals are to research to enlighten and to teach to inspire.

He regularly collaborates with other scholars in his specialty areas and enjoys working with students on their research projects at both undergraduate and graduate levels. When not at work, Jun loves running, swimming, doing push-ups, tweaking codes, and playing board games (go, chess). He primarily uses and is still learning R, Stata, and Python for methodological, pedagogical, and substantive projects. His work has appeared in, among others, Comparative Education Review, Social Forces, Social Science & Medicine, Sociological Methods and Research, Social Science Research, and The Stata Journal. He has also published two books--Ordered Regression Models and Modern Applied Regressions--on regression analysis of categorical and limited response variables with Chapman & Hall/CRC.

He is a founder and the inaugural president of the Asian and Pacific Islander Faculty and Staff Association and the founder and organizer of the Data Analytics Forum (formerly the Applied Statistics and R) at Ball State University, and the newsletter editor of the International Chinese Sociological Association.

His favorite reads include American Journal of Public Health, Lancet, New England Journal of Medicine, Statistical Science, The American Statistician, general science, Scientific American, Asian Nation, and PBS's Asian American History site,  Check webmails, have Zoom meetings, and author github.

Representative Publications

Books

Jun Xu. 2023. Modern Applied Regressions: Bayesian and Frequentist Analysis of Categorical and Limited Response Variables with R and Stan (amazon, routledge)

Fullerton, Andrew S. and Jun Xu. 2016. Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives, (amazon, routledge) Chapman and Hall/CRC of Taylor and Francis. Here are some supplementary materials for this book.

Data and Statistical Science

Xu, Jun, Shawn Bauldry and Andrew S. Fullerton. 2022. "Bayesian Approaches to Assessing the Parallel Lines Assumption in Cumulative Ordered Logit Models," Sociological Methods & Research

Fullerton, Andrew S. and Jun Xu 2018. "Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables." Sociological Methods & Research, 47(2):169-206.

Xu, Jun and Andrew Fullerton. 2014. "Comparing, Confounding, or Clarifying? Alternative Measures of Statistical Group Comparisons in Binary Regression Models." Chinese Sociological Review, 46(2):91-119

Xu, Jun and J. Scott Long. 2005b. "Using the Delta Method to Construct Confidence Intervals for Predicted Probabilities, Rates, and Discrete Change." Unpublished Manuscript. 

Xu, Jun and J. Scott Long. 2005a. "Confidence Intervals for Predicted Outcomes in Regression Models for Categorical Outcomes." The Stata Journal, 5(4):537-559

Statistical Programming

SPost9: Stata Package for post-estimation analysis of categorical and limited response variable models (with J. Scott Long; read the two papers listed above for technical details )

grcompare: Stata package for making group comparisons for binary regression models (please see the 2014 CSR paper for technical details)

gencrm: Stata command for estimating generalized continuation ratio model (with Shawn Bauldry and Andrew Fullerton)

sigcoef: Stata command for counting significant coefficients 

stdcoef.R: R function for producing partially-standardized or fully-standardized coefficients for commonly used categorical and limited response variables models.

Health Research

Gong, Fang and Jun Xu. 2021. "Ethnic Disparities in Mental Health among Asian Americans: Evidence from a National Sample." Journal of Health Disparities Research and Practice, 14(3), 6

Gong, Fang, Jun Xu, Kaori Fujihiro and David Takeuchi. 2011. "A Life Course Perspective on Migration and Mental Health among Asian Immigrants: The Role of Human Agency." Social Science & Medicine, 73(11):1618-26

Kaori Fujishiro, Jun Xu, Fang Gong. 2010. "What Does Occupation Represent As an Indicator of Socioeconomic Status? Exploring Occupational Prestige and Health." Social Science & Medicine, 71(12):2100-2107.

Asian American Studies

Gong, Fang, Jun Xu, and David Takeuchi. 2017. "Racial and Ethnic Differences in Perceptions of Everyday Discrimination." Sociology of Race and Ethnicity, 3(4):6-21

Xu, Jun and Jennifer Lee. 2013. "Marginalized Model Minority? An Empirical Examination of the Racial Triangulation of Asian Americans." Social Forces, 91(4):1363-1397. 

Xu, Jun. 2005 "Why Do Minority Participate Less? The Effects of Immigration, Education, and Electoral Process on the Voter Registration and Turnout of Asian Americans." Social Science Research, 34(4):682-702.

Xu, Jun. 2002. "The Political Behavior of Asian Americans: A Theoretical Approach." Journal of Political and Military Sociology: 30:71-89

China Studies


Xu, Jun, Wei Zhao, and Fang Gong. 2021.  “Market Transition, Multidimensional Socioeconomic Status, and Health Disparities in Urban China.” Sociological Perspectives.


Zhao, Wei and Jun Xu. 2020. “Visible and Invisible Hands Intertwined: State-Market Symbiotic Interactions and Changing Income Inequality in Urban China.” Social Science Research, 91