Conference talk, 2020 IMPS Virtual Conference, Online
Using survey data from a high school sample, in this study, we explore item-level response times, and response sequence and styles using process and meta data, and build on previously recommended methods for detection of careless response behavior.
Conference talk (symposium), NCME, San Francisco, CA (cancelled)
Building upon previous change-point analysis methods, joint modeling of item responses and response times is applied to detect various types of aberrant response behavior and to estimate the point of change in behavior.
Conference talk, 2019 International Meeting of the Psychometric Society, New York, NY
In this study, we propose the application of change-point analysis through a hierarchical framework for responses and response times. By leveraging information from both item responses and response times, we demonstrate this application to a real dataset of assessment data.
Conference talk, 2018 International Meeting of the Psychometric Society, New York, NY
In this study we show that the lack of universal DIF effect size measure makes interpretation of power of DIF detection difficult, and develop a set of criteria for a desirable DIF effect size measure.
Conference talk, Ideas in Testing Research Seminar, Chicago, IL
In this study we show that, in general, a DIF item with low-discrimination is more likely to be mistakenly chosen into the anchor set; even if it is tested for DIF, it is difficult to detect the DIF effect.
Conference talk, 2015 National Council of Measurement in Education, Washington, DC
This study employs a two-step procedure which selects an anchor set and assesses the items outside the anchor for DIF (M-IT/M-PA; Wang & Shih, 2010). Results show that accuracy rates in selecting an anchor with multiple imputation were generally higher than with full-information maximum likelihood.