Seock‐Ho Kim

2.3k total citations
61 papers, 1.6k citations indexed

About

Seock‐Ho Kim is a scholar working on Management Science and Operations Research, Computer Networks and Communications and Statistics and Probability. According to data from OpenAlex, Seock‐Ho Kim has authored 61 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Management Science and Operations Research, 31 papers in Computer Networks and Communications and 22 papers in Statistics and Probability. Recurrent topics in Seock‐Ho Kim's work include Psychometric Methodologies and Testing (42 papers), Advanced Statistical Modeling Techniques (31 papers) and Statistical Methods and Bayesian Inference (15 papers). Seock‐Ho Kim is often cited by papers focused on Psychometric Methodologies and Testing (42 papers), Advanced Statistical Modeling Techniques (31 papers) and Statistical Methods and Bayesian Inference (15 papers). Seock‐Ho Kim collaborates with scholars based in United States, South Korea and Türkiye. Seock‐Ho Kim's co-authors include Allan S. Cohen, Frank B. Baker, Sun‐Joo Cho, Feiming Li, James A. Wollack, Laura M. Stapleton, R. J. De Ayala, C. Mitchell Dayton, Sedat Şen and Paula J. Schwanenflugel and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Geriatrics Society and Psychometrika.

In The Last Decade

Seock‐Ho Kim

59 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seock‐Ho Kim United States 22 867 589 364 280 210 61 1.6k
Terry A. Ackerman United States 19 1.0k 1.2× 585 1.0× 402 1.1× 286 1.0× 215 1.0× 62 2.2k
H. Jane Rogers United States 11 871 1.0× 471 0.8× 262 0.7× 278 1.0× 241 1.1× 20 1.4k
Louis A. Roussos United States 19 900 1.0× 524 0.9× 298 0.8× 268 1.0× 244 1.2× 46 1.5k
Wendy M. Yen United States 18 1.1k 1.3× 623 1.1× 364 1.0× 279 1.0× 346 1.6× 43 2.1k
David Magis Belgium 20 516 0.6× 268 0.5× 250 0.7× 219 0.8× 177 0.8× 73 1.4k
Fumiko Samejima United States 15 1.1k 1.3× 599 1.0× 482 1.3× 354 1.3× 198 0.9× 29 2.3k
Christine E. DeMars United States 23 817 0.9× 334 0.6× 270 0.7× 514 1.8× 375 1.8× 72 2.1k
Michael J. Kolen United States 26 1.8k 2.1× 938 1.6× 865 2.4× 302 1.1× 347 1.7× 85 3.2k
Sun‐Joo Cho United States 19 331 0.4× 220 0.4× 288 0.8× 177 0.6× 269 1.3× 75 1.1k
Akihito Kamata United States 18 328 0.4× 203 0.3× 192 0.5× 156 0.6× 213 1.0× 72 1.2k

Countries citing papers authored by Seock‐Ho Kim

Since Specialization
Citations

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

Fields of papers citing papers by Seock‐Ho Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seock‐Ho Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Seock‐Ho Kim. A scholar is included among the top collaborators of Seock‐Ho 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 Seock‐Ho Kim. Seock‐Ho 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.
Kim, Seock‐Ho, et al.. (2021). A note on the three methods of item analysis. Behaviormetrika. 48(2). 345–367. 3 indexed citations
2.
Şen, Sedat, Allan S. Cohen, & Seock‐Ho Kim. (2020). A Short Note on Obtaining Item Parameter Estimates of IRT Models with Bayesian Estimation in Mplus. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi. 11(3). 266–282. 2 indexed citations
3.
Li, Yumeng, Jupil Ko, Cathleen N. Brown, et al.. (2017). Does chronic ankle instability influence lower extremity muscle activation of females during landing?. Journal of Electromyography and Kinesiology. 38. 81–87. 34 indexed citations
4.
Baker, Frank B. & Seock‐Ho Kim. (2017). The Basics of Item Response Theory Using R. CERN Document Server (European Organization for Nuclear Research). 149 indexed citations
5.
Cho, Sun‐Joo, Allan S. Cohen, Seock‐Ho Kim, & Brian A. Bottge. (2010). Latent Transition Analysis With a Mixture Item Response Theory Measurement Model. Applied Psychological Measurement. 34(7). 483–504. 21 indexed citations
6.
Schwanenflugel, Paula J., et al.. (2004). A Construct Validation Study of Phonological Awareness for Children Entering Prekindergarten. Journal of Psychoeducational Assessment. 22(4). 304–319. 24 indexed citations
7.
Kim, Seock‐Ho. (2002). A Continuation Ratio Model for Ordered Category Items.. 5 indexed citations
8.
Cohen, Allan S., Michael T. Kane, & Seock‐Ho Kim. (2001). The Precision of Simulation Study Results. Applied Psychological Measurement. 25(2). 136–145. 19 indexed citations
9.
Kim, Seock‐Ho. (2000). An Investigation of the Likelihood Ratio Test, the Mantel Test, and the Generalized Mantel-Haenszel Test of DIF.. Journal of Medical Microbiology. 29(2). 121–30. 2 indexed citations
10.
Kim, Seock‐Ho & Allan S. Cohen. (1999). Accuracy of Parameter Estimation in Gibbs Sampling under the Two-Parameter Logistic Model.. 3 indexed citations
11.
Cohen, Allan S. & Seock‐Ho Kim. (1998). An Investigation of Linking Methods Under the Graded Response Model. Applied Psychological Measurement. 22(2). 116–130. 28 indexed citations
12.
Kim, Seock‐Ho & Allan S. Cohen. (1998). On the Behrens-Fisher Problem: A Review. Journal of Educational and Behavioral Statistics. 23(4). 356–356. 8 indexed citations
13.
Cohen, Allan S., Seock‐Ho Kim, & James A. Wollack. (1998). A Comparison of Item Response Theory and Observed Score DIF Detection Measures for the Graded Response Model..
14.
Kim, Seock‐Ho & Allan S. Cohen. (1998). Detection of Differential Item Functioning Under the Graded Response Model With the Likelihood Ratio Test. Applied Psychological Measurement. 22(4). 345–355. 80 indexed citations
15.
Kim, Seock‐Ho & Allan S. Cohen. (1997). A Comparison of Linking and Concurrent Calibration under the Graded Response Model. American Educational Research Association Annual Meeting. 1997(1). 3 indexed citations
16.
Kim, Seock‐Ho & Allan S. Cohen. (1995). A Minimum Chi Square Method for Equating Tests under the Graded Response Model.. Applied Psychological Measurement. 19(2). 208–10. 5 indexed citations
17.
Kim, Seock‐Ho, Allan S. Cohen, Frank B. Baker, Michael J. Subkoviak, & Tom Leonard. (1994). An Investigation of Hierarchical Bayes Procedures in Item Response Theory. Psychometrika. 59(3). 405–421. 20 indexed citations
18.
Cohen, Allan S. & Seock‐Ho Kim. (1992). Detecting Calculator Effects on Item Performance. Applied Measurement in Education. 5(4). 303–320. 11 indexed citations
19.
Cohen, Allan S., Seock‐Ho Kim, & Michael J. Subkoviak. (1991). Influence of Prior Distributions on Detection of DIF. Journal of Educational Measurement. 28(1). 49–59. 7 indexed citations
20.
Kim, Seock‐Ho, Frank B. Baker, & Michael J. Subkoviak. (1989). The 1/ kn rules in the minimum logit chi‐square estimation procedure when small samples are used. British Journal of Mathematical and Statistical Psychology. 42(1). 113–126. 3 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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