Literature DB >> 27269482

Joint Modeling of Ability and Differential Speed Using Responses and Response Times.

Jean-Paul Fox1, Sukaesi Marianti2.   

Abstract

With computerized testing, it is possible to record both the responses of test takers to test questions (i.e., items) and the amount of time spent by a test taker in responding to each question. Various models have been proposed that take into account both test-taker ability and working speed, with the many models assuming a constant working speed throughout the test. The constant working speed assumption may be inappropriate for various reasons. For example, a test taker may need to adjust the pace due to time mismanagement, or a test taker who started out working too fast may reduce the working speed to improve accuracy. A model is proposed here that allows for variable working speed. An illustration of the model using the Amsterdam Chess Test data is provided.

Entities:  

Keywords:  Joint model; latent growth model; response times; variable speed

Mesh:

Year:  2016        PMID: 27269482     DOI: 10.1080/00273171.2016.1171128

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


  14 in total

1.  Using Response Times to Model Not-Reached Items due to Time Limits.

Authors:  Steffi Pohl; Esther Ulitzsch; Matthias von Davier
Journal:  Psychometrika       Date:  2019-05-03       Impact factor: 2.500

2.  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

3.  Bridging Models of Biometric and Psychometric Assessment: A Three-Way Joint Modeling Approach of Item Responses, Response Times, and Gaze Fixation Counts.

Authors:  Kaiwen Man; Jeffrey R Harring; Peida Zhan
Journal:  Appl Psychol Meas       Date:  2022-05-27

4.  Application of Change Point Analysis of Response Time Data to Detect Test Speededness.

Authors:  Ying Cheng; Can Shao
Journal:  Educ Psychol Meas       Date:  2021-09-20       Impact factor: 3.088

5.  On the Speed Sensitivity Parameter in the Lognormal Model for Response Times and Implications for High-Stakes Measurement Practice.

Authors:  Benjamin Becker; Dries Debeer; Sebastian Weirich; Frank Goldhammer
Journal:  Appl Psychol Meas       Date:  2021-06-09

6.  Estimation of Person Ability under Rapid and Effortful Responding.

Authors:  Georgios Sideridis; Maisa Alahmadi
Journal:  J Intell       Date:  2022-09-13

7.  The Role of Response Times on the Measurement of Mental Ability.

Authors:  Georgios Sideridis; Maisaa Taleb S Alahmadi
Journal:  Front Psychol       Date:  2022-06-17

8.  Multidimensional latent trait linear mixed model: an application in clinical studies with multivariate longitudinal outcomes.

Authors:  Jue Wang; Sheng Luo
Journal:  Stat Med       Date:  2017-06-01       Impact factor: 2.373

9.  Assessing Preknowledge Cheating via Innovative Measures: A Multiple-Group Analysis of Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts.

Authors:  Kaiwen Man; Jeffrey R Harring
Journal:  Educ Psychol Meas       Date:  2020-10-31       Impact factor: 3.088

10.  A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data.

Authors:  Esther Ulitzsch; Steffi Pohl; Lale Khorramdel; Ulf Kroehne; Matthias von Davier
Journal:  Psychometrika       Date:  2021-12-02       Impact factor: 2.290

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