Ben Wright, Rasch Measurement, and Cognitive Psychology

  • Ryan P. Bowles
  • Karen M. Schmidt
  • Tracy L. Kline
  • Kevin J. Grimm
Part of the Springer Series in Measurement Science and Technology book series (SSMST)


Ben Wright has influenced cognitive psychology both through his own work and through his training of cognitive psychologists. We provide several examples of our efforts to apply the Rasch measurement techniques Ben taught us to cognitive psychology. We describe results from studies employing fit analysis, differential item functioning analysis, Rasch item design techniques, and item linking. These studies address several aspects of human cognition, including spatial visualization, working memory, vocabulary ability, foreign language learning, and cognitive aging. None of these results would be possible without the Rasch measurement techniques we learned from Ben Wright.


  1. Andrich, D. (1978). A rating scale formulation for ordered response categories. Psychometrika, 43, 561–573.CrossRefGoogle Scholar
  2. Bayroff, A. G., & Fuchs, E. F. (1968). The armed services vocational aptitude battery. Proceedings of the Annual Convention of the American Psychological Association, 3, 635–636.Google Scholar
  3. Bowles, R. P. & McArdle, J. J. (2000). An Item Response Theory (IRT) analysis of WAIS and WJ-R sub-scales. In McArdle, J. J (Ed.), A summary of recent results from the National Growth and Change Study (NGCS). Department of Psychology, University of Virginia, Appendix to NIH Grant AG7467, National Institute on Aging.Google Scholar
  4. Bowles, R. P., & Salthouse, T. A. (2003). Assessing the age-related effects of proactive interference on working memory span tasks using the Rasch model. Psychology and Aging, 18, 608–615.CrossRefPubMedGoogle Scholar
  5. Campbell, S. K., Kolobe, T. H. A., Wright, B. D., & Linacre, J. M. (2002). Validity of the test of infant motor performance for prediction of 6-, 9- and 12-month scores on the Alberta Infant Motor Scale. Developmental Medicine and Child Neurology, 44, 263–272.CrossRefPubMedGoogle Scholar
  6. Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. New York: Cambridge University Press.CrossRefGoogle Scholar
  7. Chang, C.-H., & Wright, B. D. (2001). Detecting unexpected variables in the MMPI-2 social introversion scale. Journal of Applied Measurement, 2, 227–240.PubMedGoogle Scholar
  8. Embretson, S. E. (1984). A general multicomponent latent trait model for response processes. Psychometrika, 49, 175–186.CrossRefGoogle Scholar
  9. Embretson, S. E. (1991). A multidimensional latent trait model for measuring learning and change. Psychometrika, 52, 495–516.CrossRefGoogle Scholar
  10. Embretson, S. E., & Schmidt McCollam, K. M. (2000a). A multicomponent Rasch model for measuring covert processes: Application to lifespan ability changes. In M. Wilson & G. Engelhard (Eds.), Objective measurement: Theory into practice (Vol. Vol. 5, pp. 203–218). Norwood: Ablex.Google Scholar
  11. Embretson, S. E., & Schmidt McCollam, K. M. (2000b). Psychometric approaches to understanding and measuring intelligence. In R. J. Sternberg (Ed.), Handbook of human intelligence (pp. 423–444). New York: Cambridge University Press.CrossRefGoogle Scholar
  12. Fischer, G. (1973). The linear logistic test model as an instrument in educational research. Acta Psychologica, 37, 359–374.CrossRefGoogle Scholar
  13. Hasher, L., & Zacks, R. (1988). Working memory, comprehension, and aging: A review and a new view. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. Vol. 22, pp. 193–226). New York: Academic Press.Google Scholar
  14. Heinemann, A. W., Linacre, J. M., Wright, B. D., Hamilton, B. B., & Granger, C. (1994). Measurement characteristics of the functional independence measure. Topics in Stroke Rehabilitation, 1, 1–15.CrossRefPubMedGoogle Scholar
  15. Joy, S., Fein, D., Kaplan, E., & Freedman, M. (2001). Quantifying qualitative features of block design performance among healthy older adults. Archives of Clinical Neuropsychology, 16, 157–170.CrossRefPubMedGoogle Scholar
  16. Kaplan, E. (1988). A process approach to neuropsychological assessment. In T. Boll & B. K. Bryant (Eds.), Clinical neuropsychology and brain function: Research, measurement, and practice (pp. 129–231). Washington, DC: American Psychological Association.Google Scholar
  17. Kaplan, E., Fein, D., Morris, D., & Delis, D. (1991). The WAIS-R as a neuropsychological instrument. San Antonio: Psychological Corporation.Google Scholar
  18. Kaufman, A. S. (1990). Assessing adolescent and adult intelligence. Boston: Allyn and Bacon.Google Scholar
  19. Kline, T. L., & Schmidt, K. M. (2005). Rasch analysis examining processing mechanisms of the object location memory test revised. Journal of Applied Measurement, 6, 382–395.PubMedGoogle Scholar
  20. Lezak, M. D. (1995). Neuropsychological assessment (3rd ed.). Oxford: Oxford University Press.Google Scholar
  21. Linacre, J. M. (1989). Facets [Computer software]. Chicago: MESA Press.Google Scholar
  22. Linacre, J. M., & Wright, B. D. (1994). Chi-square fit statistics. Rasch Measurement Transactions, 8, 350.Google Scholar
  23. Linacre, J. M., & Wright, B. D. (2001). Winsteps (Version 3.02) [Computer software]. Chicago: MESA Press.Google Scholar
  24. Lunz, M. E., Bergstrom, B. A., & Wright, B. D. (1992). The effect of review on student ability and test efficiency for computerized adaptive tests. Applied Psychological Measurement, 16, 33–40.CrossRefGoogle Scholar
  25. May, C. P., Hasher, L., & Kane, M. J. (1999). The role of interference in memory span. Memory and Cognition, 27, 759–767.CrossRefPubMedGoogle Scholar
  26. McArdle, J. J., Ferrer-Caja, E., Hamagami, F., & Woodcock, R. W. (2002). Comparative longitudinal structural analyses of the growth and decline of multiple intellectual abilities over the life span. Developmental Psychology, 38, 115–142.CrossRefPubMedGoogle Scholar
  27. McArdle, J., Grimm, K., Hamagami, F., Bowles, R., & Meredith, W. (2009). Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement. Psychological Methods, 14(2), 126–149.CrossRefPubMedPubMedCentralGoogle Scholar
  28. McArdle, J. J., Hamagami, F., Meredith, W., & Bradway, K. P. (2000). Modeling the dynamic hypotheses of Gf-Gc theory using longitudinal life-span data. Learning and Individual Differences, 12, 53–79.CrossRefGoogle Scholar
  29. McArdle, J. J., & Nesselroade, J. R. (2003). Growth curve analysis in contemporary research. In J. Schinka & W. Velicer (Eds.), Comprehensive handbook of psychology, Research methods in psychology (Vol. Vol II, pp. 447–480). New York: Pergamon.Google Scholar
  30. McCollam, K. M. (1997). The modifiability of age differences in spatial visualization (Doctoral dissertation, University of Kansas, 1997). Dissertation Abstracts International, 59, 1409.Google Scholar
  31. McGrew, K. S., Werder, J. K., & Woodcock, R. W. (1991). WJ-R technical manual. Allen: DLM.Google Scholar
  32. Ohio State University Foreign Language Center. (2002). MultiCAT. Columbus: Ohio State University.Google Scholar
  33. Perline, R., Wright, B. D., & Wainer, H. (1979). The Rasch model as additive conjoint measurement. Applied Psychological Measurement, 3, 237–256.CrossRefGoogle Scholar
  34. Rost, J. (1990). Rasch models in latent classes: An integration of two approaches to item analysis. Applied Psychological Measurement, 14, 271–282.CrossRefGoogle Scholar
  35. Salthouse, T. A. (1987). Sources of age-related individual differences in block design tests. Intelligence, 11, 245–262.CrossRefGoogle Scholar
  36. Schmidt McCollam, K. M. (1998). Latent trait and latent class models. In G. M. Marcoulides (Ed.), Modern methods for business research (pp. 23–46). Mahwah: Erlbaum.Google Scholar
  37. Shepard, R. N., & Feng, C. (1972). A chronometric study of mental paper folding. Cognitive Psychology, 3, 338–243.CrossRefGoogle Scholar
  38. Shepard, R. N., & Metzler, J. (1971). Mental rotation of three-dimensional objects. Science, 171, 701–703.CrossRefPubMedGoogle Scholar
  39. Silverman, I., & Eals, M. (1992). Sex differences in spatial abilities: Evolutionary theory and data. In J. Barkow, L. Cosmides, & J. Tooby (Eds.), The adapted mind: Evolutionary psychology and the generation of culture (pp. 487–503). New York: Oxford University Press.Google Scholar
  40. Stone, M. H., & Wright, B. D. (1983). Measuring attending behavior and short-term memory with Knox’s cube test. Educational and Psychological Measurement, 43, 803–814.CrossRefGoogle Scholar
  41. Storandt, M. (1977). Age, ability level, and method of administering and scoring the WAIS. Journal of Gerontology, 32, 175–178.CrossRefGoogle Scholar
  42. Troyer, A. K., Cullum, C. M., Smernoff, E. N., & Kozora, E. (1994). Age effects on block design: Qualitative performance features and extended-time effects. Neuropsychology, 8, 95–99.CrossRefGoogle Scholar
  43. Verhaeghen, P., & Salthouse, T. A. (1997). Meta-analyses of age-cognition relations in adulthood: Estimates of linear and nonlinear age effects and structural models. Psychological Bulletin, 122, 231–249.CrossRefPubMedGoogle Scholar
  44. Wechsler, D. (1981). Wechsler adult intelligence scale- revised. New York: Psychological Corporation.Google Scholar
  45. Wilde, M. C., Boake, C., & Sherer, M. (2000). Wechsler adult intelligence scale- revised block design broken configuration errors in nonpenetrating traumatic brain injury. Applied Neuropsychology, 7, 208–214.CrossRefPubMedGoogle Scholar
  46. Woodcock, R. W., & Johnson, M. B. (1989). Woodcock-Johnson psycho-educational battery- revised. Allen, TX: DLM.Google Scholar
  47. Wright, B. D. (1977). Solving measurement problems with the Rasch model. Journal of Educational Measurement, 14, 97–116.CrossRefGoogle Scholar
  48. Wright, B. D. (1994). Data analysis and fit. Rasch Measurement Transactions, 7, 324.Google Scholar
  49. Wright, B. D. (1999). Fundamental measurement for psychology. In S. E. Embretson & S. L. Hershberger (Eds.), The new rules of measurement: What every psychologist and educator should know (pp. 65–104). Mahwah: Erlbaum.Google Scholar
  50. Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. Chicago: MESA Press.Google Scholar
  51. Wright, B. D., Mead, R., & Draba, R. (1976). Detecting and correcting test item bias with a logistic response model (MESA Research Memorandum No. 22). Chicago: MESA Psychometric Laboratory.Google Scholar
  52. Wright, B. D., & Stone, M. A. (1979). Best test design. Chicago: MESA Press.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ryan P. Bowles
    • 1
  • Karen M. Schmidt
    • 2
  • Tracy L. Kline
    • 3
  • Kevin J. Grimm
    • 4
  1. 1.Department of Human Development and Family StudiesMichigan State UniversityEast LansingUSA
  2. 2.Department of PsychologyUniversity of VirginiaCharlottesvilleUSA
  3. 3.RTI International, Research Triangle ParkDurhamUSA
  4. 4.Department of PsychologyArizona State UniversityTempeUSA

Personalised recommendations