Skip to main content

Response Time Data as Validity Evidence: Has It Lived Up To Its Promise and, If Not, What Would It Take to Do So

  • Chapter
  • First Online:
Understanding and Investigating Response Processes in Validation Research

Part of the book series: Social Indicators Research Series ((SINS,volume 69))

Abstract

As a convenient data source from computerized tests, response time could also be very informative evidence for the validity of test scores, offering an opportunity for insights into parts of the test that test takers linger over and other parts of the test where they glide through the material. Given these hopes for, and expectations of, response time data, we should critically evaluate how such data are studied and more importantly, to what extent this type of data lives up to its promise. We begin this chapter by defining response time and briefly discussing its use as validity evidence. We then describe the typical uses of response time data and review the different approaches to studying response time data in various research. The chapter closes with an evaluation of response time data as validity evidence and suggests the conditions that would facilitate better use of response data for validation purposes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • American Educational Research Association, American Psychological Association, & National Council on Measurement in Education [AERA, APA, & NCME]. (2014). Standards for educational and psychological testing (5th ed.). Washington, DC: American Educational Research Association.

    Google Scholar 

  • Bergstrom, B., Gershon, R., & Lunz, M. E. (1994, April). Computerized adaptive testing exploring test taker response time using hierarchical linear modeling. Paper presented at the annual meeting of the National Council on Measurement in Education, New Orleans, LA.

    Google Scholar 

  • Chan, S.-C., Lu, T.-S., & Tsai, R.-C. (2014). Incorporating RT to analyze test data with mixture structural equation modeling. Psychological Testing, 61, 463–488.

    Google Scholar 

  • Dennis, I., & Evans, J. S. B. T. (1996). The speed-error trade-off problem in psychometric testing. British Journal of Psychology, 87, 105–129. doi:10.1111/j.2044-8295.1996.tb02579.x.

    Article  Google Scholar 

  • Dodonova, Y. A., & Dodonova, Y. S. (2013). Faster on easy items, more accurate on difficult ones: Cognitive ability and performance on a task of varying difficulty. Intelligence, 41, 1–10. doi:10.1016/j.intell.2012.10.003.

    Article  Google Scholar 

  • Fan, Z., Wang, C., Chang, H.-H., & Douglas, J. (2012). Utilizing response time distributions for item selection in CAT. Journal of Educational and Behavioral Statistics, 37, 655–670. doi:10.3102/1076998611422912.

    Article  Google Scholar 

  • Ferrando, P. J., & Lorenzo-Seva, U. (2007). An item response theory model for incorporating response time data in binary personality items. Applied Psychological Measurement, 31, 525–543. doi:10.1177/0146621606295197.

    Article  Google Scholar 

  • Fox, J.-P., Entink, R. K., & van der Linden, W. (2007). Modeling of responses and response times with the package cirt. Journal of Statistical Software, 20, 1–14. doi:10.18637/jss.v020.i07.

    Google Scholar 

  • Gierl, M. J., & Leighton, J. P. (2007). Defining cognitive diagnostic assessment in education. In J. P. Leighton & M. J. Gierl (Eds.), Cognitive diagnostic assessment for education: Theory and applications (pp. 3–18). Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Gorin, J. S. (2006). Test design with cognition in mind. Educational Measurement: Issues and Practice, 25, 21–35. doi:10.1111/j.1745-3992.2006.00076.x.

    Article  Google Scholar 

  • Gulliksen, H. (1950). Theory of mental tests. New York, NY: Wiley.

    Book  Google Scholar 

  • Gvozdenko, E., & Chambers, D. (2007). Beyond test accuracy: Benefits of measuring response time in computerised testing. Australasian Journal of Educational Technology, 23, 542–558. doi:10.14742/ajet.v23i4.1251.

    Article  Google Scholar 

  • Halkitis, P. N., & Jones, J. P. (1996, April). Estimating testing time: The effects of item characteristics on response latency. Paper presented at the annual meeting of the American Educational Research Association, New York.

    Google Scholar 

  • Hess, B. J., Johnston, M. M., & Lipner, R. S. (2013). The impact of item format and test taker characteristics on response times. International Journal of Testing, 13, 295–313. doi:10.1080/15305058.2012.760098.

    Article  Google Scholar 

  • Huff, K. L., & Sireci, S. G. (2001). Validity issues in computer-based testing. Educational Measurement: Issues and Practice, 20, 16–25. doi:10.1111/j.1745-3992.2001.tb00066.x.

    Article  Google Scholar 

  • Jang, E. E. (2009). Cognitive diagnostic assessment of L2 reading comprehension ability: Validity arguments for Fusion Model application to LanguEdge assessment. Language Testing, 26, 31–73. doi:10.1177/0265532208097336.

    Article  Google Scholar 

  • Klein Entink, R. H., Kuhn, J.-T., Hornke, L. F., & Fox, J.-P. (2009). Evaluating cognitive theory: A joint modeling approach using responses and response times. Psychological Methods, 14, 54–75. doi:10.1037/a0014877.

    Article  Google Scholar 

  • Kong, X. J., Wise, S. L., & Bhola, D. S. (2007). Setting the response time threshold parameter to differentiate solution behavior from rapid-guessing behavior. Educational and Psychological Measurement, 67, 606–619. doi:10.1177/0013164406294779.

    Article  Google Scholar 

  • Kahraman, N., Cuddy, M. M., & Clauser, B. E. (2013). Modeling pacing behavior and test speededness using latent growth curve models. Applied Psychological Measurement, 37, 343–360. doi:10.1177/0146621613477236.

    Article  Google Scholar 

  • Lasry, N., Watkins, J., Mazur, E., & Ibrahim, A. (2013). Response times to conceptual questions. American Journal of Physics, 81, 703. doi:10.1119/1.4812583.

    Article  Google Scholar 

  • Lee, Y.-H., & Chen, H. (2011). A review of recent response-time analyses in educational testing. Psychological Test and Assessment Modeling, 53, 359–379.

    Google Scholar 

  • Lee, Y.-H., & Haberman, S. J. (2016). Investigating test-taking behaviors using timing and process data. International Journal of Testing, 16, 240–267. doi:10.1080/15305058.2015.1085385.

    Article  Google Scholar 

  • Leijten, M., & Van Waes, L. (2013). Keystroke logging in writing research: Using Inputlog to analyze and visualize writing processes. Written Communication, 30, 358–392. doi:10.1177/0741088313491692.

    Article  Google Scholar 

  • Lu, Y., & Sireci, S. G. (2007). Validity issues in test speededness. Educational Measurement: Issues and Practice, 26, 29–37. doi:10.1111/j.1745-3992.2007.00106.x.

    Article  Google Scholar 

  • Lyons-Thomas, J., Liu, Y., & Zumbo, B. D. (2014). Validation practices in the social, behavioral, and health sciences: A synthesis of syntheses. In B. D. Zumbo & E. K. H. Chan (Eds.), Validity and validation in social, behavioral, and health sciences (pp. 313–319). New York, NY: Springer.

    Google Scholar 

  • Marianti, S., Fox, J.-P., Avetisyan, M., Veldkamp, B. P., & Tijmstra, J. (2014). Testing for aberrant behavior in response time modeling. Journal of Educational and Behavioral Statistics, 39, 426–451. doi:10.3102/1076998614559412.

    Article  Google Scholar 

  • Meng, X.-B., Tao, J., & Chang, H.-H. (2015). A conditional joint modeling approach for locally dependent item responses and response times. Journal of Educational Measurement, 52, 1–27. doi:10.1111/jedm.12060.

    Article  Google Scholar 

  • Messick, S. (1989). Validity. In R. Linn (Ed.), Educational measurement (3rd ed., pp. 13–103). Washington, DC: American Council on Education.

    Google Scholar 

  • Meyer, J. P. (2010). A mixture Rasch model with item response time components. Applied Psychological Measurement, 34, 521–538. doi:10.1177/0146621609355451.

    Article  Google Scholar 

  • Mislevy, R. J. (1989). Foundations of a new test theory. ETS Research Report Series, 1982(2), i-32.

    Google Scholar 

  • Molenaar, D. (2015). The value of response times in item response modeling. Measurement: Interdisciplinary Research and Perspectives, 13, 177–181. doi:10.1080/15366367.2015.1105073.

    Google Scholar 

  • Molenaar, D., Tuerlinckx, F., & van der Maas, H. L. J. (2015). A bivariate generalized linear item response theory modeling framework to the analysis of responses and response times. Multivariate Behavioral Research, 50, 56–74. doi:10.1080/00273171.2014.962684.

    Article  Google Scholar 

  • Parshall, C. G., Mittelholtz, D. J., & Miller, T. R. (1994, April). Response latency: An investigation into determinants of item-level timing. Paper presented at the Annual Meeting of the National Council on Measurement in Education, New Orleans.

    Google Scholar 

  • Qian, H., Staniewska, D., Reckase, M., & Woo, A. (2016). Using response time to detect item preknowledge in computer-based licensure examinations. Educational Measurement: Issues and Practice, 35, 38–47. doi:10.1111/emip.12102.

    Article  Google Scholar 

  • Ranger, J., & Kuhn, J.-T. (2013). Analyzing response times in tests with rank correlation approaches. Journal of Educational and Behavioral Statistics, 38, 61–80. doi:10.3102/1076998611431086.

    Article  Google Scholar 

  • Ranger, J., & Kuhn, J.-T. (2014). Testing fit of latent trait models for responses and response times in tests. Psychological Test and Assessment Modeling, 56, 382–404.

    Google Scholar 

  • Ranger, J., & Kuhn, J.-T. (2015). Modeling information accumulation in psychological tests using item response times. Journal of Educational and Behavioral Statistics, 40, 274–306. doi:10.3102/1076998615583903.

    Article  Google Scholar 

  • Ranger, J., & Kuhn, J.-T. (2016). A mixture proportional hazards model with random effects for response times in tests. Educational and Psychological Measurement, 76, 562–586. doi:10.1177/0013164415598347.

    Article  Google Scholar 

  • Ranger, J., Kuhn, J.-T., & Gaviria, J.-L. (2015). A race model for responses and response times in tests. Psychometrika, 80, 791–810. doi:10.1007/s11336-014-9427-8.

    Article  Google Scholar 

  • Ranger, J., & Ortner, T. M. (2012). The case of dependency of responses and response times: A modeling approach based on standard latent trait models. Psychological Test and Assessment Modeling, 54, 128–148.

    Google Scholar 

  • Ratcliff, R. (2014). Measuring psychometric functions with the diffusion model. Journal of Experimental Psychology. Human Perception and Performance, 40, 870–888. doi:10.1037/a0034954.

    Article  Google Scholar 

  • Ratcliff, R., van Zandt, T., & McKoon, G. (1999). Connectionist and diffusion models of reaction time. Psychological Review, 106, 261–300.

    Article  Google Scholar 

  • Scherer, R., Greiff, S., & Hautamäki, J. (2015). Exploring the relation between time on task and ability in complex problem solving. Intelligence, 48, 37–50. doi:10.1016/j.intell.2014.10.003.

    Article  Google Scholar 

  • Schnipke, D. L., & Scrams, D. J. (1997). Modeling item response times with a two-state mixture model: A new method of measuring speededness. Journal of Educational Measurement, 34, 213–232. doi:10.1111/j.1745-3984.1997.tb00516.x.

    Article  Google Scholar 

  • Schnipke, D. L., & Scrams, D. J. (2002). Exploring issues of examinee behavior: Insights gained from response-time analyses. In C. N. Mills, M. Potenza, J. J. Fremer, & W. Ward (Eds.), Computer-based testing: Building the foundation for future assessments (pp. 237–266). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc..

    Google Scholar 

  • Siem, F. M. (1996). The use of response latencies to enhance self-report personality measures. Military Psychology, 8, 15–27. doi:10.1207/s15327876mp0801_2.

    Article  Google Scholar 

  • Suvorov, R. (2015). The use of eye tracking in research on video-based second language (L2) listening assessment: A comparison of context videos and content videos. Language Testing, 32, 463–483. doi:10.1177/0265532214562099.

    Article  Google Scholar 

  • Thissen, D. (1983). Timed testing: An approach using item response theory. In D. J. Weiss (Ed.), New horizons in testing: Latent trait theory and computerized adaptive testing (pp. 179–203). New York, NY: Academic Press.

    Google Scholar 

  • Thomas, M. H. (2006). Modeling differential pacing trajectories in high stakes computer adaptive testing using hierarchical linear modeling and structural equation modeling. Unpublished doctoral dissertation. The University of North Carolina at Greensboro, Greensboro, NC.

    Google Scholar 

  • van der Linden, W. J. (2006). A lognormal model for response times on test items. Journal of Educational and Behavioral Statistics, 31, 181–204. doi:10.3102/10769986031002181.

    Article  Google Scholar 

  • van der Linden, W. J. (2007). A hierarchical framework for modeling speed and accuracy on test items. Psychometrika, 72, 287–308. doi:10.1007/s11336-006-1478-z.

    Article  Google Scholar 

  • van der Linden, W. J. (2009). Conceptual issues in response-time modeling. Journal of Educational Measurement, 46, 247–272. doi:10.1111/j.1745-3984.2009.00080.x.

    Article  Google Scholar 

  • van der Linden, W. J. (2011). Setting time limits on tests. Applied Psychological Measurement, 35, 183–199. doi:10.1177/0146621610391648.

    Article  Google Scholar 

  • van der Linden, W. J., & Guo, F. (2008). Bayesian procedures for identifying aberrant response-time patterns in adaptive testing. Psychometrika, 73, 365–384. doi:10.1007/s11336-007-9046-8.

    Article  Google Scholar 

  • van der Linden, W. J., & Hambleton, R. K. (Eds.). (1997). Handbook of modern item response theory. New York, NY: Springer-Verlag.

    Google Scholar 

  • van der Linden, W. J., Klein Entink, R. H., & Fox, J.-P. (2010). IRT parameter estimation with response times as collateral information. Applied Psychological Measurement, 34, 327–347. doi:10.1177/0146621609349800.

    Article  Google Scholar 

  • van der Linden, W. J., Scrams, D. J., & Schnipke, D. L. (1999). Using response-time constraints to control for differential speededness in computerized adaptive testing. Applied Psychological Measurement, 23, 195–210. doi:10.1177/01466219922031329.

    Article  Google Scholar 

  • van der Maas, H. L. J., Molenaar, D., Maris, G., Kievit, R. A., & Borsboom, D. (2011). Cognitive psychology meets psychometric theory: On the relation between process models for decision making and latent variable models for individual differences. Psychological Review, 118, 339–356. doi:10.1037/a0022749.

    Article  Google Scholar 

  • Voss, A., Nagler, M., & Lerche, V. (2013). Diffusion models in experimental psychology: A practical introduction. Experimental Psychology, 60, 385–402. doi:10.1027/1618-3169/a000218.

    Article  Google Scholar 

  • Wang, C., Chang, H.-H., & Douglas, J. A. (2013). The linear transformation model with frailties for the analysis of item response times. The British Journal of Mathematical and Statistical Psychology, 66, 144–168. doi:10.1111/j.2044-8317.2012.02045.x.

    Article  Google Scholar 

  • Wang, T. (2005). Development and calibration of an item response model that incorporates response time. Applied Psychological Measurement, 29, 323–339. doi:10.1177/0146621605275984.

    Article  Google Scholar 

  • Wickelgren, W. A. (1977). Speed-accuracy tradeoff and information processing dynamics. Acta Psychologica, 41, 67–85. doi:10.1016/0001-6918(77)90012-9.

    Article  Google Scholar 

  • Wise, S. L. (2014). The utility of adaptive testing in addressing the problem of unmotivated test takers. Journal of Computerized Adaptive Testing, 2, 1–17. doi:10.7333/jcat.v2i0.30.

    Google Scholar 

  • Wise, S. L., & DeMars, C. E. (2006). An application of item response time: The effort-moderated IRT model. Journal of Educational Measurement, 43, 19–38. doi:10.1111/j.1745-3984.2006.00002.x.

    Article  Google Scholar 

  • Wise, S. L., & Kong, X. (2005). Response time effort: A new measure of test taker motivation in computer-based tests. Applied Measurement in Education, 18, 163–183. doi:10.1207/s15324818ame1802_2.

    Article  Google Scholar 

  • Yang, X. (2007). Methods of identifying individual guessers from item response data. Educational and Psychological Measurement, 67, 745–764. doi:10.1177/0013164406296978.

    Article  Google Scholar 

  • Zenisky, A. L., & Baldwin, P. (2006). Using item response time data in test development and validation: Research with beginning computer users, Center for educational assessment report No. 593. Amherst, MA: University of Massachusetts, School of Education.

    Google Scholar 

  • Zumbo, B. D. (2007). Validity: Foundational issues and statistical methodology. In C. R. Rao & S. Sinharay (Eds.), Handbook of statistics, Psychometrics (Vol. 26, pp. 45–79). The NetherlandsAmsterdam: Elsevier Science B.V..

    Google Scholar 

  • Zumbo, B. D., & Chan, E. K. H. (Eds.). (2014). Validity and validation in social, behavioral, and health sciences. New York, NY: Springer.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhi Li .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Li, Z., Banerjee, J., Zumbo, B.D. (2017). Response Time Data as Validity Evidence: Has It Lived Up To Its Promise and, If Not, What Would It Take to Do So. In: Zumbo, B., Hubley, A. (eds) Understanding and Investigating Response Processes in Validation Research. Social Indicators Research Series, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-319-56129-5_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-56129-5_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56128-8

  • Online ISBN: 978-3-319-56129-5

  • eBook Packages: Social SciencesSocial Sciences (R0)

Publish with us

Policies and ethics