2025 and in press (* denotes graduate students)
Park, J.*, Jin, I., & Jeon, M. (in press). Analysis of Log Data from an International Online Educational Assessment System: A Multi-state Survival Modeling Approach to Reaction Time Between and Across Action Sequences. Psychometrika.
De Carolis, L.* & Jeon. M. (in press). Network Approaches to Binary Assessment Data: Network Psychometrics vs. Latent Space Item Response Model. Educational and Psychological Measurement.
Yoon, M., Yang, H., & Jeon, M. (in press). Discovering action insights from large-scale assessment log data using machine learning. Scientific Reports.
Huang, Y.*, Luo, J.*, Shetty, V. , & Jeon, M. (in press). The power of social talk: A longitudinal network analysis of conversations in fostering interdisciplinary collaboration. Journal of Clinical and Translational Science.
Kang, I. & Jeon, M. (in press). Integration of latent space and confirmatory factor analysis to explain unexplained person-item interactions. Psychological Methods.
Resch, J.*, Baugh, S., Duan, H.*, Tang, J.*, Madison, M., Cotterell, M., & Jeon, M. (in press). Bayesian transition diagnostic classification models with Polya-gamma augmentation. Psychometrika.
Srinivasan, J., Cobian, K. & Jeon, M. (in press). Psychometric properties of the science self-efficacy scale for STEMM undergraduates. European Journal of Investigation in Health, Psychology and Education.
Ren, J.*, Luo, J.*, Huang, Y.*, Shetty, V., & Jeon, M. (in press). Mapping the mHealth nexus: A semantic analysis of mHealth scholars’ research propensities following an interdisciplinary training institute. Applied Sciences.
Zeng, B.*, Wen, H. & Jeon, M. (in press). Ideal point or dominance process? Unfolding tree approaches to Likert scale data with multi-process models. Multivariate Behavioral Research.
Kang, I. & Jeon, M. (in press). Multidimensional latent space item response models: A note on the relativity of conditional dependence. Psychometrika.
2024
Madison, M. J., Jeon, M. Cotterell, M. E., Haab, S.*, & Zor, S.* (in press). TDCM: An R package for estimating longitudinal diagnostic classification models. Multivariate Behavioral Research.
Zeng, B.*, Jeon, M., & Wen, H. (2024). How does item wording affect participants' responses? Evidence from IRT analysis. Frontiers in Psychology. 15, 1304870.
Huang, S., Luo, J.* & Jeon, M. (2024). A response time-based mixture item response theory model for dynamic item-response strategies. Behavior Research Methods. 57, 54.
Yi, S.*, Kim, M.*, Park, J., Jin, I-H., & Jeon, M. (in press). Point process cluster analysis in latent space item response models for school survey data. Journal of the Royal Statistical Society: Series A.
Yoon, M., Yang, H., & Jeon, M. (2024). A novel prediction method for patients at risk of developing depressive symptoms using a small data set. Plos One. 19, e0303889.
Kang, I. & Jeon, M. (2024). A recent development of a network approach to assessment data: Latent space item response model for intelligence studies. Journal of Intelligence. 12, 38.
Jeon, M. & Schweinberger, M. (2024) A latent process model for monitoring progress towards hard-to-measure targets, with applications to mental health and online educational assessments. The Annals of Applied Statistics. 18, 2123-2146.
Kim, N., Jeon, M., & Partchev, I. (2024). Conditional dependencies across slow and fast item responses: with a latent space item response modeling approach. Journal of Intelligence. 12, 23.
Luo, J.*, Jeon, M., & Shen, H. (2024). Chinese university students' growth in critical thinking: Accounting for school transition and selection effects. Chinese/English Journal of Educational Measurement and Evaluation. 5, Article 3.
Ho, E.*, Seltzer, M. & Jeon, M. (2024). Are teachers meeting students’ needs in untracked science classrooms? Evidence based on a causal inferential approach. Plos One. 19, e0300587.
Lee, M.*, Seo, Y-S., & Jeon, M. (2024). Item response analysis of a structured mixture item response model with mirt package in R. Psych. 6, 377-400.
2023
Jin, I-H., Yun, J., Kim, H.*, & Jeon, M. (2023). Latent space accumulator model for analyzing bipartite networks with connection-times and its applications to item response data. Stat. 12, e632.
Ho, E.*, & Jeon, M. (2023). IntMap: Shiny App for latent space item response models for educational assessments. Psych. 5, 1140-1155
Park, J.*, Jin, I., & Jeon, M. (2023). How social networks influence human behavior: An integrated latent space approach for differential social influence. Psychometrika. DOI: 10.1007/s11336-023-09934-5
Kang, I.*, Jeon, M., & Partchev, I. (2023). A latent space diffusion Item Response Theory model to explore conditional dependence between responses and response times. Psychometrika. 88, 830–864.
Jeon, M. (2023). Commentary: Explore conditional dependencies in item response tree data. Psychometrika. 803–808.
Luo, J.*, De Carolis, L.*, Zeng, B.*, & Jeon, M. (2023). Bayesian estimation of latent space item response models with JAGS, Stan, and NIMBLE in R. Psych., 5, 396-415.
2022
Langi, M.* & Jeon, M. (2022). Identifying and supporting academically low-performing schools in a developing country: An application of a specialized multilevel IRT model to PISA-D assessment data. Psychometrika, 88, 332-356.
Huang, S.* & Jeon, M. (2022). Modern applications of cross-classified random effects models in social and behavioral research: Illustration with R package PLmixed. Frontiers in Psychology, 13, 976964.
Luo, J.*, Jeon, M., Lee, M.*, Ho, E.*, Pfammatter, A. F., Shetty, V., & Spring, B. (2022). Relationships between changing communication networks and changing perceptions of psychological safety in a team science setting: Analysis with actor-oriented social network models. Plos One, 17: e0273899.
Jin, I-H., Jeon, M., Schweinberger, M., Yun, J., & Lin, L. (2022). Multilevel network item response modeling for discovering differences between innovation and regular school systems in Korea. Journal of the Royal Statistical Society: Series C, 71, 1225–1244.
Chi, W. E.,* Huang, S.,* Jeon, M., Park, E. S., Melguizo, T., & Kezar, A. (2022). A practical guide to causal mediation analysis: Illustration with a comprehensive college transition program and nonprogram peer and faculty interactions. Frontiers in Education., 7, 886722.
Go, D.*, Jeon, M., Lee, S.*, Jin, I-H, & Park, H-J. (2022). Analyzing differences between parent- and self-report measures with a latent space approach. Plos One, 17: e0269376.
Park, J., Jeon, Y.*, Shin, M., Jeon, M., & Jin, I-H. (2022). Bayesian shrinkage for functional network models with applications to longitudinal item response data. Journal of Computational and Graphical Statistics, 31, 360-377.
2021
Ho, E.*, Jeon, M., Lee, M.*, Luo, J.*, Pfammatter, A. F., Shetty, V., & Spring, B. (2021). Fostering interdisciplinary collaboration: A longitudinal social network analysis of the NIH mHealth Training Institutes. Journal of Clinical and Translational Science, 5, E191.
Jeon, M., Jin, I-H., Schweinberger, M., & Baugh, S.* (2021). Mapping unobserved item-response interactions: A latent space item response model with interaction maps. Psychometrika, 86, 378-403
Jeon, M., De Boeck, P., Luo, J.∗, Li, X., & Lu, Z-L. (2021). Modeling within-item dependencies in parallel data on test responses and brain activation. Psychometrika, 86, 239-271.
Zhang, S., Bergner, Y, DiTrapani, D., & Jeon, M. (2021). Modeling the interaction between resilience and ability in assessments with allowances for multiple attempts. Computers in Human Behavior, 122, 106847.
De Boeck, P., DeKay, M., Gore, R., & Jeon, M. (2021). Commentary: The trees and the forest: Investigating variability surrounding an aggregate result. Theory & Psychology., 31, 399-404.
2020
Jeon, M., DeBoeck, P., Li, X, & Lu, Z-L. (2020). Trivariate theory of mind data analysis with a conditional joint modeling approach. Psychometrika, 85, 398-436.
Jeon, M., Draney, K., Wilson, M., & Sun, Y.∗ (2020). Investigation of adolescents’ developmental stages in deductive reasoning: An application of a specialized mixture IRT approach. Behavior Research Methods, 52, 224-235.
Montaya, A.∗ & Jeon, M. (2020). MIMIC DIF models as moderated mediation models. Applied Psychological Measurement, 44, 118-136.
2019
Khorramdel, L., Jeon, M., & Wang, L. (2019). Advances in modeling response styles and related phenomena. British Journal of Mathematical and Statistical Psychology, 72, 393-400.
De Boeck, P., Jeon, M. & Gore, R., (2019). Commentary: Beyond registration pre and post. Computational Brain & Behavior, 2, 183-186.
Rocca, C., Wilson, M., Jeon, M., & Foster, D. G. (2019). Stability of retrospective pregnancy intention reporting among women with unwanted pregnancies in the United States. Maternal and Child Health Journal, 23, 1547-1555.
Jeon, M. & De Boeck, P. (2019). Evaluation on types of invariance in studying extreme response bias with an IRTree approach. British Journal of Mathematical and Statistical Psychology, 72, 517-537.
Jeon, M. (2019). Specialized confirmatory mixture IRT modeling for multidimensional tests. Psychological Test and Assessment Modeling, 61, 91-123.
De Boeck & Jeon, M. (2019). An overview of models for response times and processes in cognitive tests. Frontiers in Applied Mathematics and Statistics, 10, 102.
Lukowski, S.∗, DiTrapani, J.∗, Rockwood, N.∗, Jeon, M., Thompson, L. A. & Petrill, S. (2019). Etiological distinction across dimensions of math anxiety. Behavior Genetics, 29, 310-316.
Rockwood, N.∗ & Jeon, M. (2019). Estimating complex measurement and growth models using the R package PLmixed. Multivariate Behavioral Research, 54, 288-306.
Jin, I-H. & Jeon, M. (2019). [co-first-authors] A doubly latent space joint model for the analysis of item response data. Psychometrika, 84, 236-260.
Jeon, M. & De Boeck, P. (2019). An analysis of an item response strategy based on knowledge retrieval. Behavior Research Methods, 51, 697-719.
Lukowski, S. L.∗, DiTrapani, J.∗, Jeon, M., Wang, Z.∗, Schenker, V. J., Doran, M. M., Hart, S. A., Mazzocc, M., Willcutt, E. G., Thompson, L. A., & Petrill, S. A. (2019). Multidimensionality in the measurement of math-specific anxiety and its relationship with mathematical skills. Learning and Individual Differences, 70, 228-235.
2018
Jeon, M., Rijmen, F., & Rabe-Hesketh, S. (2018). CFA models with a general factor and multiple sets of secondary factors. Psychometrika., 83, 785-808.
Hughes, M. L., Agrigoroaei, S., Jeon, M., Bruzzese, M. & Lachman, M. E. (2018). Change in cognitive performance from midlife into old age: Findings from the midlife in the united states (MIDUS) study. Journal of the International Neuropsychological Society, 24, 805-820.
De Boeck, P. & Jeon, M. (2018). Perceived crisis and reforms: Issues, explanations, and remedies. Psychological Bulletin, 144, 757-777.
DiTrapani, J.*, Rockwood, N.* & Jeon, M. (2018). Explanatory IRT analysis using the SPIRIT macro in SPSS. The Quantitative Methods for Psychology, 14, 81-98.
Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E.-J., Berk, R., Bollen,K. A., Brembs, B., Brown, L., Camerer, C., Cesarini, D., Chambers, C. D., Clyde, M., Cook, T. D., De Boeck, P., Dienes, Z., Dreber, A., Easwaran, K., Efferson, C., Fehr, E., Fidler, F., Field, A. P., Forster, M., George, E. I., Gonzalez, R., Goodman, S., Green, E., Green, D. P., Greenwald, A., Hadfield, J. D., Hedges, L. V., Held, L., Ho, T.–H., Hoijtink, H., Jones, J. H., Hruschka, D. J., Imai, K., Imbens, G., Ioannidis, J. P. A., Jeon, M., Kirchler, M., Laibson, D., List, J., Little, R., Lupia, A., Machery, E., Maxwell, S. E., McCarthy, M., Moore, D., Morgan, S. L., Munafo M., Nakagawa, S., Nyhan, B., Parker, T. H., Pericchi, L., Perugini, M., Rouder, J., Rousseau, J., Savalei, V., Schobrodt, F. D., Sellke, T., Sinclair, B., Tingley, D., Van Zandt, T., Vazire, S., Watts, D. J., Winship, C., Wolpert, R. L., Xie, Y., Young, C., Zinman, J., & Johnson, V. E. (2018). Redefine Statistical Significance. Nature Human Behavior, 2, 6-10.
Jeon, M. (2018). A constrained confirmatory mixture IRT model: Extensions and estimation of the Saltus model using Mplus. The Quantitative Methods for Psychology, 14, 120-136.
Tijmstra, J., Bolsinova, M. A., & Jeon, M. (2018). Generalized mixture IRT models with different item-response structures: A case study using Likert-scale data. Behavior Research Methods, 50, 2325-2344.
Yoon, H-I., Jeon, M., Kim, H-R., Jeong, Y-H., Kim, D-G. & Han, J-S. (2018). Spatial variation of bone biomechanical properties around a dental implant using nanoindentation: A case study. Journal of the Mechanical Behavior of Biomedical Materials, 79, 168-172.
Thorn, B. E., Eyer, J. C. Van Dyke, B. P. Torres, C. A. Burns, J. W., Kim, M., Newman, A. K., Campbell, L. C., Anderson, B., Block, P. R., Bobrow, B. J., FAHA, F., Brooks, R., Burton, T. T.,Cheavens, J. S., DeMonte, C. M., DeMonte, W. D., Edwards, C. S., Jeon, M. , Mulla, M., Penn, T., Smith, L. J., Tucker, D. (2018). Literacy-adapted cognitive-behavioral therapy vs. education for chronic pain at low-income clinics: A randomized controlled trial. Annals of Internal Medicine, 168, 471-480.
Jeon, M., Kaufman, C. & Rabe-Hesketh, S. (2018). Monte Carlo local likelihood approximation. Biostatistics, 20, 164-179.
2017
Irons, J. L., Jeon, M., & Leber, A. B. (2017). Pre-stimulus pupil dilation and the preparatory control of attention. PLOS One, 12, e0188787.
Jeon, M. & Rockwood, N.* (2017). Estimating generalized linear mixed models with factor structures using the R Package PLmixed. Applied Psychological Measurement. 42, 173 - 174.
DiTrapani, J.*, Rockwood, N.* & Jeon, M. (2017). IRT analysis using the SPIRIT macro in SPSS. Applied Psychological Measurement, 42, 173 - 174.
Jeon, M. & De Boeck, P. (2017). Decision qualities of Bayes factor and p-value based hypothesis testing. Psychological Methods, 22, 340-360.
Jeon, M., Rijmen, F. & Rabe-Hesketh, S. (2017). A variational maximization-maximization algorithm for generalized linear mixed models with crossed random effects. Psychometrika, 82, 693-716.
Jeon, M., De Boeck, P. & van der Linden, W.J. (2017). Modeling answer change behavior: An application of a generalized item response tree model. Journal of Educational and Behavioral Statistics, 42, 467-490.
Fields, H. W., Kim, D-G., Jeon, M., Firestone, A. R., Sun. Z., Shanker, S., Mercado, A. M., Deguchi, T., & Vig, K. W. L. (2017). Evaluation of objective structured clinical examination for advanced orthodontic education 12 years after introduction. American Journal of Orthodontics and Dentofacial Orthopedics, 151, 840-850.
2016
Bishop, B.* & Jeon, M. (2016). [Book Review] A review of missing data analysis in practice. Psychometrika, 81, 1164-1167.
Jeon, M. & De Boeck, P. (2016). A generalized item response tree model for psychological assessments. Behavior Research Methods, 48, 1070-1085.
Jeon, M. & Rabe-Hesketh, S. (2016). An autoregressive growth model for longitudinal item analysis. Psychometrika, 81, 830-850
Jeon, M. & Rijmen, F. (2016). A modular approach for item response theory modeling with the R package FLIRT. Behavior Research Methods, 48, 742-755.
Koch, T., Schultze, M., Jeon, M., Nussbeck, F., Praetorius, A-K. & Eid, M. (2016). A cross-classified CFA-MTMM model for structurally different and non-independent interchangeable methods. Multivariate Behavioral Research, 51, 67-85.
DiTrapani, J.*, Jeon, M., De Boeck, P., & Partchev, I. (2016). Attempting to differentiate fast and slow intelligence: Using generalized item response trees to examine the role of speed on intelligence tests. Intelligence, 56, 82-92.
Rijmen, F., Jeon, M., & Rabe-Hesketh, S. (2016). Variational Approximation methods for IRT, In W.J. van der Linden & R. K. Hambleton (Eds). Handbook of Modern Item Response Theory (2nd ed.), volume 2, (pp. 259-270). New York, NY: Chapman & Hall.
2014-2015
Jeon, M. (2015). Differential response speed: Is it really a nuisance? Measurement: Interdisciplinary Research and Perspectives, 13. 169-172.
Ray, T. Y, McGraw, S., Sun, Z., Jeon, M., Johnson, T., Cheffins, K., Daegling, D., & Kim, D-G. (2015). Mandibular bone mineral density variation in sympatric cercopithecoids: Associations with diet and feeding behavior. Archives of Oral Biology, 60, 1714-1720.
Rijmen, F., Jeon, M., Rabe-Hesketh, S. & von Davier, M. (2014). A third order item response theory model for modeling the effects of domains and subdomains in large-scale educational assessment surveys. Journal of Educational and Behavioral Statistics. 39, 235-256.
Jeon, M. & Rijmen, F. (2014). Recent developments in maximum likelihood estimation of MTMM models for categorical data. Frontiers in Psychology, 5, article 269.
Jeon, M., Rijmen, F. & Rabe-Hesketh, S. (2014). Flexible item response theory modeling with IRT. Applied Psychological Measurement, 38, 404-405.
Jeon, M., Draney, K., & Wilson, M. (2014). Multidimensional Saltus linear logistic test model for modeling children’s cognitive development. In Millsap, R.E., Bolt, D.M., van der Ark, L.A., & Wang, W.-C. (Eds). Quantitative Psychology Research: Proceedings of the 78th Annual Meeting of the Psychometric Society, (pp.73-90). Springer.
Rijmen, F., Jeon, M., von Davier, M. & Rabe-Hesketh, S. (2014). A general psychometric approach for educational survey assessments: Flexible statistical models and efficient estimation methods. In Rutkowski, D., von Davier, M. & Rutkowski, D. (Eds). A Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis, (pp. 583-606). London: Chapman Hall/CRC Press.
2011-2013
Jeon, M., Rijmen, F. & Rabe-Hesketh, S. (2013). Modeling differential item functioning using a generalization of the multiple-group bifactor model. Journal of Educational and Behavioral Statistics, 38, 32-60.
Rijmen, F. & Jeon, M. (2013). Fitting an item response theory model with random item effects across groups by a variational approximation method. The Annals of Operations Research, 206, 647-662.
Jeon, M. & Rabe-Hesketh, S. (2012). Profile-likelihood approach for estimating generalized linear mixed models with factor structures. Journal of Educational and Behavioral Statistics, 37, 518-542.
van der Linden, W.J. & Jeon, M. (2012). Modeling answer changes on test items. Journal of Educational and Behavioral Statistics, 37, 180-199.
van der Linden, W.J., Jeon, M., & Ferrara, S. (2011). A paradox in the study of the benefits of test-item review. Journal of Educational Measurement, 48, 380-398.
Draney, K. & Jeon, M. (2011). Investigating the Saltus model as a tool for setting standards. Psychological Testing and Assessment Modeling, 53, 486-498.
-2009
Jeon, M., Lee, G., Hwang, J.W., & Kang, S.J. (2009). Estimating reliability of school-level scores using multilevel and generalizability theory models. Asia Pacific Education Review, 10, 149-158.
Lee, G., Park, I.Y., & Jeon, M. (2009). Testlet response models for item response theory true score equating. Korean Journal of Educational Evaluation, 22, 871-887.
Lee, G., Park, D.S., Nam, M., Kim, M., & Jeon, M. (2009). Cheating proof testing system (CPTS) and its validity. Korean Journal of Educational Evaluation, 22, 265-290.
Kim, Y., Rye, H., Namgung, J., Kim, I., & Jeon, M. (2007). Development of school education satisfaction survey instruments for students and parents. Korean Journal of Educational Evaluation, 20, 1-27.
Kang, S.J. & Jeon, M. (2006). Cross-level interaction effects between the high school equalization policy and peer relationships on high school students’ self-esteem. Journal of Korean Education, 33, 121-140.
Kang, S.J. & Jeon, M. (2006). Differences between the high school equalization and non-equalization regions: structural relationships between self-esteem, family income, and academic achievements. Korean Journal of Educational Research, 44, 195-221.
Jeon, M. & Kang, S.J. (2005). A comparison of multilevel models in parameter estimation: two- and three-level nested and cross classified models. Korean Journal of Educational Evaluation, 18, 123-147.