Jee‐Seon Kim

1.4k total citations
42 papers, 895 citations indexed

About

Jee‐Seon Kim is a scholar working on Statistics and Probability, Management Science and Operations Research and General Health Professions. According to data from OpenAlex, Jee‐Seon Kim has authored 42 papers receiving a total of 895 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Statistics and Probability, 7 papers in Management Science and Operations Research and 6 papers in General Health Professions. Recurrent topics in Jee‐Seon Kim's work include Advanced Causal Inference Techniques (8 papers), Statistical Methods and Bayesian Inference (7 papers) and Psychometric Methodologies and Testing (7 papers). Jee‐Seon Kim is often cited by papers focused on Advanced Causal Inference Techniques (8 papers), Statistical Methods and Bayesian Inference (7 papers) and Psychometric Methodologies and Testing (7 papers). Jee‐Seon Kim collaborates with scholars based in United States, Sweden and Netherlands. Jee‐Seon Kim's co-authors include Daniel M. Bolt, Edward W. Frees, Dane B. Cook, Kelli F. Koltyn, Jacob D. Meyer, Aaron J. Stegner, Laura D. Ellingson, Eric Knuth, Ana C. Stephens and Işıl Işler and has published in prestigious journals such as Medicine & Science in Sports & Exercise, Psychophysiology and Medicine.

In The Last Decade

Jee‐Seon Kim

40 papers receiving 835 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jee‐Seon Kim United States 13 202 196 125 119 118 42 895
Robert Gould United States 17 108 0.5× 290 1.5× 91 0.7× 34 0.3× 37 0.3× 33 1.1k
Simon Grund Germany 16 127 0.6× 193 1.0× 19 0.2× 63 0.5× 55 0.5× 31 814
W. Todd Rogers Canada 22 413 2.0× 89 0.5× 98 0.8× 229 1.9× 42 0.4× 83 1.9k
Barbara Forsyth United States 14 52 0.3× 49 0.3× 60 0.5× 125 1.1× 74 0.6× 19 915
Martin Hecht Germany 21 146 0.7× 155 0.8× 53 0.4× 186 1.6× 39 0.3× 78 1.2k
Brian Hess United States 19 134 0.7× 34 0.2× 59 0.5× 66 0.6× 70 0.6× 63 1.3k
Cornelia Zeisser Canada 7 138 0.7× 34 0.2× 78 0.6× 56 0.5× 28 0.2× 10 1.0k
Gordon P. Brooks United States 9 171 0.8× 50 0.3× 27 0.2× 47 0.4× 36 0.3× 37 951
Mark Reiser United States 15 484 2.4× 148 0.8× 24 0.2× 121 1.0× 47 0.4× 28 1.5k
Patrick Johnson United States 18 161 0.8× 58 0.3× 85 0.7× 41 0.3× 15 0.1× 57 1.1k

Countries citing papers authored by Jee‐Seon Kim

Since Specialization
Citations

This map shows the geographic impact of Jee‐Seon Kim'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 Jee‐Seon Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jee‐Seon Kim more than expected).

Fields of papers citing papers by Jee‐Seon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jee‐Seon Kim. 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 Jee‐Seon Kim. The network helps show where Jee‐Seon Kim may publish in the future.

Co-authorship network of co-authors of Jee‐Seon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Jee‐Seon Kim. A scholar is included among the top collaborators of Jee‐Seon Kim 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 Jee‐Seon Kim. Jee‐Seon Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Molfenter, Todd, et al.. (2025). Assessing the comparative effectiveness of ECHO and coaching implementation strategies in a jail/provider MOUD implementation trial. Implementation Science. 20(1). 7–7. 1 indexed citations
2.
Bolt, Daniel M., et al.. (2024). Curvilinearity in the Reference Composite and Practical Implications for Measurement. Journal of Educational Measurement. 61(3). 511–541.
3.
Wiberg, Marie, Dylan Molenaar, Jorge González, Jee‐Seon Kim, & Heungsun Hwang. (2023). Quantitative Psychology. Springer proceedings in mathematics & statistics. 2 indexed citations
4.
Molfenter, Todd, Nora Jacobson, Jee‐Seon Kim, et al.. (2023). Building medication for opioid use disorder prescriber capacity during the opioid epidemic: Prescriber recruitment trends and methods. Journal of Substance Use and Addiction Treatment. 147. 208975–208975. 2 indexed citations
5.
Kim, Jee‐Seon, et al.. (2022). Estimating Heterogeneous Treatment Effects Within Latent Class Multilevel Models: A Bayesian Approach. Journal of Educational and Behavioral Statistics. 48(1). 3–36. 3 indexed citations
6.
Kim, Jee‐Seon, et al.. (2022). Extending the actor-partner interdependence model to accommodate multivariate dyadic data using latent variables.. Psychological Methods. 29(5). 890–918. 3 indexed citations
7.
Loh, Wen Wei & Jee‐Seon Kim. (2022). Evaluating sensitivity to classification uncertainty in latent subgroup effect analyses. BMC Medical Research Methodology. 22(1). 247–247. 1 indexed citations
8.
Kwekkeboom, Kristine L., et al.. (2020). How does art making work? Testing the hypothesized mechanisms of art making on pain experience. Complementary Therapies in Clinical Practice. 40. 101200–101200. 3 indexed citations
9.
Knudsen, Hannah K., Randall Brown, Nora Jacobson, et al.. (2018). Pharmacotherapy, Resource Needs, and Physician Recruitment Practices in Substance Use Disorder Treatment Programs. Journal of Addiction Medicine. 13(1). 28–34. 6 indexed citations
10.
Molfenter, Todd, Hannah K. Knudsen, Randall Brown, et al.. (2017). Test of a workforce development intervention to expand opioid use disorder treatment pharmacotherapy prescribers: protocol for a cluster randomized trial. Implementation Science. 12(1). 135–135. 11 indexed citations
11.
Meyer, Jacob D., Kelli F. Koltyn, Aaron J. Stegner, Jee‐Seon Kim, & Dane B. Cook. (2016). Influence of Exercise Intensity for Improving Depressed Mood in Depression: A Dose-Response Study. Behavior Therapy. 47(4). 527–537. 103 indexed citations
12.
Meyer, Jacob D., Kelli F. Koltyn, Aaron J. Stegner, Jee‐Seon Kim, & Dane B. Cook. (2016). Relationships between serum BDNF and the antidepressant effect of acute exercise in depressed women. Psychoneuroendocrinology. 74. 286–294. 34 indexed citations
13.
Meyer, Jacob D., Laura D. Ellingson, Kelli F. Koltyn, et al.. (2016). Psychobiological Responses to Preferred and Prescribed Intensity Exercise in Major Depressive Disorder. Medicine & Science in Sports & Exercise. 48(11). 2207–2215. 31 indexed citations
14.
Keller, Bryan, et al.. (2013). Propensity Score Estimation with Data Mining Techniques: Alternatives to Logistic Regression.. Society for Research on Educational Effectiveness. 1 indexed citations
15.
Kim, Jee‐Seon, et al.. (2013). Within-Cluster and Across-Cluster Matching with Observational Multilevel Data.. Society for Research on Educational Effectiveness. 1 indexed citations
16.
Keller, Bryan, Jee‐Seon Kim, & Peter M. Steiner. (2013). Abstract: Data Mining Alternatives to Logistic Regression for Propensity Score Estimation: Neural Networks and Support Vector Machines. Multivariate Behavioral Research. 48(1). 164–164. 9 indexed citations
17.
Kim, Jee‐Seon. (2006). Using the Distractor Categories of Multiple‐Choice Items to Improve IRT Linking. Journal of Educational Measurement. 43(3). 193–213. 5 indexed citations
18.
Kim, Jee‐Seon & Edward W. Frees. (2006). Omitted Variables in Multilevel Models. Psychometrika. 71(4). 659–690. 49 indexed citations
19.
Kim, Jee‐Seon & Bradley A. Hanson. (2002). Test Equating Under the Multiple-Choice Model. Applied Psychological Measurement. 26(3). 255–270. 19 indexed citations
20.
Kim, Jee‐Seon & Ulf Böckenholt. (2000). Modeling stage-sequential change in ordered categorical responses.. Psychological Methods. 5(3). 380–400. 6 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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