Hongwen Guo

Hongwen Guo Principal research scientist Educational Testing Service (ETS) Princeton, NJ, 08541 USA

I have worked on or been consulted by many testing programs and research projects at ETS. My current research focuses on statistical modeling of item responses and process data and issues occurred in research and operations in testing programs, related to score quality, fairness, validity, and reliability. I have about 50 publications and 80 presentations in the areas of psychometrics, statistics, and mathematics. My working experiences also include teaching courses in these three areas.

RECENT PUBLICATIONS

Ercikan, K., Guo, H., & He, Q. (2020, accepted). Use of response process data to inform group comparison and fairness research. Educational Assessment.

Guo, H., Zhang, M., Deane, P., & Bennett, R. (2020, in press). Using Writing Logs to Help Validate Assessments for Learning. The LAK20 companion proceedings.

Guo, H., Ling, & G., Frankel, L. (2019, in press). Using existing data to inform development of new item types.

(ETS Research Report RR-XX-XX). Princeton, NJ : ETS.

Guo, H. & Dorans, N. (2019, in press). Using weighted sum scores to close the gap between DIF practice and theory. Journal of Educational Measurement. https://onlinelibrary.wiley.com/doi/full/10.1111/ jedm.12258

Guo, H. & Dorans, N. (2019). A note on using weighted sum scores in the P-DIF statistic. (ETS Research Report RR-19-32). Princeton, NJ : ETS.

Guo, H., Zu, J., & Kyllonen, P. (2019). Consistency of NRM-based scoring rules across cohorts for a situational judgment test. Psychological Test and Assessment Modeling, 61, 207-225.

Guo, H., Zhang, M., Deane, P., & Bennett, R. (2019). Writing process di erences of subgroups re ected in keystroke logs. Journal of Educational and Behavioral Statistics. https://journals.sagepub.com/doi/ 10.3102/1076998619856590 

Wang, X., Liu, Y., Robin, F., & Guo, H. (2019). A comparison of methods for detecting examinee preknowledge of Items. International Journal of Testing, 19, 207-226. DOI: 10.1080/15305058.2019.1610886

Zhang, M., Zhu, M., Deane, P. & Guo, H. (2019). Identifying and comparing writing process patterns using keystroke logs. International meeting of Psychometric society proceeding. In: Wiberg M., Culpepper S., Janssen R., Gonzalez J., Molenaar D. (eds) Quantitative Psychology. IMPS 2017. Springer Proceedings in Mathematics & Statistics, vol 265. Springer, Cham.

Guo, H. & Dorans, N. (2019). Observed scores as matching variables in Di erential Item Functioning under the 1PL and 2PL model: Population Results. (ETS Research Report RR-19-06). Princeton, NJ : ETS.

Guo, H., Zu, J. & Kyllonen, P. (2018). A simulation-based method for nding the optimal number of options for multiple-choice items on a test. (ETS Research Report RR-18-22). Princeton, NJ : ETS.

Lu, R. & Guo, H. (2018). A Simulation Study to Compare Nonequivalent Groups With Anchor Test Equating and Pseudo-Equivalent Group Linking. (ETS Research Report RR-18-08). Princeton, NJ : ETS.

Guo, H., Deane, P., Rijn, P., Zhang, M., & Bennett, R. (2018). Modeling basic writing processes from keystroke logs. Journal of Educational Measurement, 55, 194-216.

Guo, H., Robin, F., & Dorans, N. (2017). Detecting Item Parameter Drift in Large Scale On-demand Testing.

Journal of Educational Measurement, 54, 265-284.

Rios, J. A., Guo, H., Mao, L., & Liu, O. L. (2017). Evaluating the impact of careless responses on aggregated scores: To lter unmotivated examinees or not? International Journal of Testing, 17, 74-104. http://dx.doi.org/10.1080/15305058.2016.1231193

Guo, H. (2017). Exploring online learning data using fractal dimensions. Research Report (ETS RR-17-15).

Guo, H. (2017). Predicting rights-only score distributions from data collected under formula score instructions. Psychometrika, 82, 1-16. DOI: 10.1007/s11336-016-9550-9

Guo, H., Zu, J., Kyllonen, P., & Schmitt, N. (2016). Evaluation of Di erent Scoring Rules for a Non-cognitive Test in Development (ETS Research Report RR-16-03). Princeton, NJ : ETS.

Guo, H., Rios, J., Haberman, S., Liu, O. L., Wang, J.,& Paek, I. (2016). A new procedure for detection of students' rapid guessing responses using response time. Applied Measurement in Education, 29, 173-183.

RECENT PRESENTATIONS

Yao, L., Zhang, M., & Guo, H. (2020, July, 14-17). Using mixture models of lognormal distributions to udnderstand keystroke logs for retype and draft writing tasks. Proposal submitted to ITC 2020.

Guo, H. & Ercikan, K. (2020, July, 14-17). Rapid-guessing behaviors within and across language-and-cultural groups. Proposal submitted to ITC 2020, within a symposium on student test taking e ort; Organizer: Gavin Brown; Discussant: Steve Wise.

Guo, H., Zhang, M., Deane, P., & Bennett, R. (2020, March 23-27). Using Writing Logs to Help Validate Assessments for Learning. LAK20. Frankfurt, Germany. Poster accepted.

Dearn, P., van Rijn, P., Guo, H., Li, C., & Zhang, M. (2020, April). Using Trait Indicators to Measure Growth on a Scenario-Based Assessment. Will be presented at the NCME Annual Meeting, San Francisco, CA.

Zhang, M., Li, C., Shinharay, S. & Guo, H. (2020, April). Providing Formative Feedback on Writing Perfor-mance to Support Test Preparation. Will be presented at the NCME Annual Meeting, San Francisco, CA.

Ercikan, K., Guo, H., & He, Q. (2020). Use of response process data to inform group comparisons and fairness research. Will be presented at the Using process data for advancing the practice and science of educational measurement symposium. Organized by Ercikan, K, chaired by Baker, at the NCME Annual Meeting, San Francisco, CA.

Zhang, M., Zhu, M., Liu, X. & Guo, H. (2020, April). Will present at the Probabilistic graphical models for writing process data coordinated session at the NCME Annual Meeting, San Francisco, CA.

Zhang, M., Liu, X., & Guo, H. (2020, April, 16). Modeling writing process using keystroke logs. Training session at the NCME Annual Meeting, San Francisco, CA.

Lu, R., Guo, H., & Dorans, N. (2020, April). Robustness of weighted di erential item functioning (DIF) statistics. Will be presented at the NCME Annual Meeting, San Francisco, CA.

Oh, H., Guo, H. & Chen, L. (2020, April). Impact of translation on item response and item response time.Will be presented at the NCME Annual Meeting, San Francisco, CA.

Chen, L., Oh, H., Guo, H. & Joo, S. (2020, April, 16-20). Evaluating test form equivalence of translated tests across language groups. Will be presented at the NCME Annual Meeting, San Francisco, CA.

Oh, H. & Guo, H. (2019, Oct). Impact of weighted sum scores on IRT ture score equating. The FASP poster session. ETS Princeton campus, NJ.

Oh, H. & Guo, H. (2019, Oct). Evaluating test form equivalence of translated tests across language groups.The FASP poster session. ETS Princeton campus, NJ.

Lu, R., Guo, H., & Dorans, N. (2019, Oct). Robustness of DIF with weighed sum scores. The FASP poster session. ETS Princeton campus, NJ.

Guo, H., Zhang, M., Deane, P., & Bennett, R. (2019, August). Statistical modeling of writing process data. Paper presented at Psychometrics, Statistics, & Data Sciences (PSDS) electronic poster session. ETS Princeton campus, NJ.

Zhang, M., Deane, P., Feng, G., & Guo, H. (2019, July). Investigating an approach to evaluating keyboarding uency. Paper presented at the 2019 ST&D Conference, New York, NY.

Ercikan, K, Guo. H, & He, Q. (2019, April). Use of response process data in large-scale assessments for cross cultural comparisons. Presented at the panel session (Chaired by K. Ercikan) at the 2019 Comparative & International Education Society. San Francisco, CA.

Guo, H. & Dorans, N. (2019, April). What the MH DIF statistics measure? Presented at the meeting of the NCME Annual Meeting, Toronto, CAN.

Guo, H., Zhang, M., Deane, P., & Bennett, R. (2019, April. NCME Award Session). Using stochastic processes to model writing processes (for Bradley Hanson Award for Contributions to Educational Measurement). Presented at the meeting of the NCME Annual Meeting, Toronto, CAN.

Oh, H., & Guo, H. (2019, April. Electronic board session). Impact of Weighted Sum Scores on IRT True Score Equating. Presented at the meeting of the NCME Annual Meeting, Toronto, CAN.

Rios, J., & Guo, H. (2019, April. Coordinated Session) Is There Di erential None ortful Responding Between Countries on an International Assessment? Presented at the meeting of the NCME Annual Meeting, Toronto, CAN.

Lu, R. & Guo, H. (2019, April. Electronic board session). A three-factor model that uni es response, time, and missing. Presented at the meeting of the NCME Annual Meeting, Toronto, CAN.

Guo, H. (2019, Feb.). Some results on PISA process data. The FPSR monthly seminar. ETS: Princeton, NJ.

Ercikan, K., Guo, H., & Gao, J. (2018, Oct. Invited talk). Possibilities and challenges in using response process data for advancing measurement. Tucker Seminar. Princeton, NJ: Educational Testing service.

Guo, H. & Dorans, N. (2018, Oct). Close the gap between DIF practice and theory. The FASP poster session.Princeton, NJ: ETS. 

Guo, H. (2018, Sept. Invited talk). Process data and writing skills. Presented at the colloquium Talk at Tsinghua University Center for Statistical Science, Beijing, China.

Guo, H., Zhang, M., Deane, P., & Bennett, R. (July, 2018. Invited session). Writing keystroke logs and their modeling. Presented at the International Meeting of the Psychometric Society, New York, NY.

Zhang, M., Zhu, M., Deane, P. & Guo, H. (July, 2018). Analyzing editing behaviors in writing using timing and process information (Poster). Presented at the International Meeting of the Psychometric Society

Guo, H., Zhang, M., Deane, P., & Bennett, R. (June, 2018. Invited session). Modeling Writing process using keystroke logs. Presented at the International Chinese Statistical Association (ICSA) meeting, New Brunswick, NJ.

Zu, J., Kyllonen, P., & Guo, H. (April, 2018). Examining the E ectiveness of Anchoring Vignettes Longitudi-nally. Paper presented at the meeting of the NCME Annual Meeting, New York, NY.

Guo, H. Zu, J., & Kyllonen, P. (April, 2018). A simulation-based method for nding the optimal number of options for multiple-choice items on a test. Paper presented at the meeting of the NCME Annual Meeting, New York, NY.

Guo, H., Zhang, M., Deane, P., & Bennett, R. (2018, Jan). Writing process di erences of subgroups re ected in keystroke logs. ETS Symposium of Keystroke Log Analysis, Princeton, NJ.

Guo, H., Deane, P., Rijn, P., Zhang, M., & Bennett, R. (2017, July). Exploring the heavy-tailed key-stroke data in writing processes. Poster session at the Society for Text & Discourse Annual Conference, Philadelphia, PA.

Guo, H., Zu, j., & Kyllonen, P. C. (2017, April). Cross validation of the NRM-scoring method for a situational judgment test. In P. Kyllonen (Chair), Psychometrics for noncognitive assessment: Unique challenges and some solutions. Symposium conducted at the meeting of the NCME Annual Meeting, San Antonio, TX.

Zu, J., Guo, H. & Kyllonen, P. C. (2016, July). Subgroup invariance of nominal response model scores for a situational judgment test. In J. Liu (Chair), The development and use of noncognitive assessment in K-12. Symposium conducted at the meeting of the Psychometric Society, Asheville, NC.

Rios, J., Miao, L., Guo, H., & Liu, L. (2016, July). Test-Taking Motivation and the Validity of Inferences from Test Scores: A Global Concern. Paper presented at the 10th Conference of the International Test Commission, Vancouver, CA.

Lin, J., Guo, H., & Jia, Y. (2016, April). Incorporating Expert Priors in Estimation of Bayesian Networks for Computer Interactive Tasks. Paper presented at the NCME Annual Meeting, Washington DC.

Guo, H. & Robin, F. (2016, April). Monitoring item drift using stochastic process control charts. Paper presented at the NCME Annual Meeting, Washington DC.

Wang, X., Robin, F., Liu, Y., Guo, H., & Dorans, N. (2016, April).  Detecting Examinee Preknowledge of Items: A Comparison of Methods. Paper presented at the NCME Annual Meeting, Washington DC.