Literature DB >> 31448968

Using Response Times for Joint Modeling of Response and Omission Behavior.

Esther Ulitzsch1, Matthias von Davier2, Steffi Pohl1.   

Abstract

For adequate modeling of missing responses, a thorough understanding of the nonresponse mechanisms is vital. As a large number of major testing programs are in the process or already have been moving to computer-based assessment, a rich body of additional data on examinee behavior becomes easily accessible. These additional data may contain valuable information on the processes associated with nonresponse. Bringing together research on item omissions with approaches for modeling response time data, we propose a framework for simultaneously modeling response behavior and omission behavior utilizing timing information for both. As such, the proposed model allows (a) to gain a deeper understanding of response and nonresponse behavior in general and, in particular, of the processes underlying item omissions in LSAs, (b) to model the processes determining the time examinees require to generate a response or to omit an item, and (c) to account for nonignorable item omissions. Parameter recovery of the proposed model is studied within a simulation study. An illustration of the model by means of an application to real data is provided.

Keywords:  Markov Chain Monte Carlo; Response times; item response theory; missing propensity; missing responses

Year:  2019        PMID: 31448968     DOI: 10.1080/00273171.2019.1643699

Source DB:  PubMed          Journal:  Multivariate Behav Res        ISSN: 0027-3171            Impact factor:   5.923


  4 in total

1.  A Multiprocess Item Response Model for Not-Reached Items due to Time Limits and Quitting.

Authors:  Esther Ulitzsch; Matthias von Davier; Steffi Pohl
Journal:  Educ Psychol Meas       Date:  2019-10-21       Impact factor: 2.821

2.  Psychometric Modelling of Longitudinal Genetically Informative Twin Data.

Authors:  Inga Schwabe; Zhengguo Gu; Jesper Tijmstra; Pete Hatemi; Steffi Pohl
Journal:  Front Genet       Date:  2019-10-16       Impact factor: 4.599

3.  Combining Clickstream Analyses and Graph-Modeled Data Clustering for Identifying Common Response Processes.

Authors:  Esther Ulitzsch; Qiwei He; Vincent Ulitzsch; Hendrik Molter; André Nichterlein; Rolf Niedermeier; Steffi Pohl
Journal:  Psychometrika       Date:  2021-02-05       Impact factor: 2.500

4.  On the Treatment of Missing Item Responses in Educational Large-Scale Assessment Data: An Illustrative Simulation Study and a Case Study Using PISA 2018 Mathematics Data.

Authors:  Alexander Robitzsch
Journal:  Eur J Investig Health Psychol Educ       Date:  2021-12-14
  4 in total

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