Chi Chang

719 total citations
20 papers, 456 citations indexed

About

Chi Chang is a scholar working on Statistics and Probability, Computer Networks and Communications and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Chi Chang has authored 20 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Statistics and Probability, 3 papers in Computer Networks and Communications and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Chi Chang's work include Statistical Methods and Bayesian Inference (3 papers), Advanced Statistical Modeling Techniques (3 papers) and Statistical Methods and Inference (3 papers). Chi Chang is often cited by papers focused on Statistical Methods and Bayesian Inference (3 papers), Advanced Statistical Modeling Techniques (3 papers) and Statistical Methods and Inference (3 papers). Chi Chang collaborates with scholars based in United States, United Kingdom and Australia. Chi Chang's co-authors include Binbin Zheng, Chin‐Hsi Lin, Mark Warschauer, Tenko Raykov, George A. Marcoulides, Yining Zhang, Thomas Jaki, M. Lee Van Horn, Joseph C. Gardiner and Richard T. Houang and has published in prestigious journals such as Journal of Consulting and Clinical Psychology, Pain and Review of Educational Research.

In The Last Decade

Chi Chang

19 papers receiving 442 citations

Peers

Chi Chang

EDUCA

DEP

SPS

Remco Feskens Netherlands

Rita Karam United States

Eva Jiménez-García Spain

José Felipe Martínez United States

Sandra Acosta United States

Amy Benjamin United States

Lihshing Leigh Wang United States

Kristen L. Brezinski United States

Jeffrey C. Wayman United States

Remco Feskens Netherlands

Chi Chang

302 ×1.7

EDUCA

67 ×0.9

211 ×2.9

DEP

101 ×1.7

SPS

40 ×0.8

Citations per year, relative to Chi Chang Chi Chang (= 1×) peers Remco Feskens

Countries citing papers authored by Chi Chang

Since Specialization

Citations

This map shows the geographic impact of Chi Chang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chi Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi Chang more than expected).

Fields of papers citing papers by Chi Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chi Chang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chi Chang. The network helps show where Chi Chang may publish in the future.

Co-authorship network of co-authors of Chi Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Chi Chang. A scholar is included among the top collaborators of Chi Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chi Chang. Chi Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jaki, Thomas, et al.. (2024). Predicting Individual Treatment Effects: Challenges and Opportunities for Machine Learning and Artificial Intelligence. KI - Künstliche Intelligenz. 39(1). 27–32.

Lee, Beatrice, et al.. (2024). Character strengths and employment in persons with disabilities: a national survey study. The Journal of Positive Psychology. 21(1). 78–88. 2 indexed citations

Ghiasi, Marzieh, Chi Chang, Amy L. Shafrir, et al.. (2024). Subgroups of pelvic pain are differentially associated with endometriosis and inflammatory comorbidities: a latent class analysis. Pain. 165(9). 2119–2129. 4 indexed citations

Chang, Chi, et al.. (2024). Assessing the impact of clerkships on the growth of clinical knowledge. Annals of Medicine. 57(1). 2443812–2443812. 1 indexed citations

Umucu, Emre, Beatrice Lee, Chi Chang, Dorota Szymkowiak, & Jack Tsai. (2024). Geographic and psychosocial correlates of homelessness or unstable housing among US veterans in the Midwest. American Journal of Community Psychology. 74(1-2). 142–151. 3 indexed citations

Zhou, Guoli, Raina N. Fichorova, Claudia Holzman, et al.. (2023). Placental circadian lincRNAs and spontaneous preterm birth. Frontiers in Genetics. 13. 1051396–1051396. 3 indexed citations

Jaki, Thomas, Elizabeth Yakes Jimenez, Alberta S. Kong, et al.. (2022). Individual differences in the effects of the ACTION-PAC intervention: an application of personalized medicine in the prevention and treatment of obesity. Journal of Behavioral Medicine. 45(2). 211–226. 5 indexed citations

Chang, Chi, et al.. (2022). glca: An R Package for Multiple-Group Latent Class Analysis. Applied Psychological Measurement. 46(5). 439–441. 22 indexed citations

Witkiewitz, Katie, et al.. (2021). Applying methods for personalized medicine to the treatment of alcohol use disorder.. Journal of Consulting and Clinical Psychology. 89(4). 288–300. 22 indexed citations

10.

Chang, Chi, Thomas Jaki, Daniel J. Feaster, et al.. (2021). A permutation test for assessing the presence of individual differences in treatment effects. Statistical Methods in Medical Research. 30(11). 2369–2381. 9 indexed citations

11.

Chang, Chi, et al.. (2020). Medical Student Progress Examination Performance and Its Relationship With Metacognition, Critical Thinking, and Self-Regulated Learning Strategies. Academic Medicine. 96(2). 278–284. 33 indexed citations

12.

Laird‐Fick, Heather, Chi Chang, Ling Wang, et al.. (2020). Assessing the growth in clinical skills using a progress clinical skills examination. PeerJ. 8. e9091–e9091. 1 indexed citations

13.

Zheng, Binbin, Chi Chang, Chin‐Hsi Lin, & Yining Zhang. (2020). Self-Efficacy, Academic Motivation, and Self-Regulation: How Do They Predict Academic Achievement for Medical Students?. Medical Science Educator. 31(1). 125–130. 40 indexed citations

14.

Chang, Chi, Joseph C. Gardiner, Richard T. Houang, & Yan-Liang Yu. (2020). Comparing multiple statistical software for multiple-indicator, multiple-cause modeling: an application of gender disparity in adult cognitive functioning using MIDUS II dataset. BMC Medical Research Methodology. 20(1). 275–275. 24 indexed citations

15.

Chang, Chi, et al.. (2020). Factors influencing readiness to change in patients with alcoholic liver disease: A cross‐sectional study. Journal of Psychiatric and Mental Health Nursing. 28(3). 344–355. 13 indexed citations

16.

Jaki, Thomas, Min-Jung Kim, Andrea Lamont, et al.. (2018). The Effects of Sample Size on the Estimation of Regression Mixture Models. Educational and Psychological Measurement. 79(2). 358–384. 31 indexed citations

17.

Raykov, Tenko, George A. Marcoulides, & Chi Chang. (2016). Examining Population Heterogeneity in Finite Mixture Settings Using Latent Variable Modeling. Structural Equation Modeling A Multidisciplinary Journal. 23(5). 726–730. 26 indexed citations

18.

Zheng, Binbin, Mark Warschauer, Chin‐Hsi Lin, & Chi Chang. (2016). Learning in One-to-One Laptop Environments. Review of Educational Research. 86(4). 1052–1084. 177 indexed citations

19.

Raykov, Tenko, et al.. (2013). Studying Differential Item Functioning via Latent Variable Modeling. Educational and Psychological Measurement. 73(5). 898–908. 19 indexed citations

20.

Raykov, Tenko, et al.. (2013). A Commentary on the Relationship Between Model Fit and Saturated Path Models in Structural Equation Modeling Applications. Educational and Psychological Measurement. 73(6). 1054–1068. 21 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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