The d2 test is a cancellation test to measure attention, visual scanning, and processing speed. It is the most frequently used test of attention in Europe. Although it has been validated using factor analytic techniques and correlational analyses, its fit to item response theory models has not been examined. We evaluated the fit of the d2 test to the Rasch Poisson Counts Model (RPCM) by examining the fit of six different scoring techniques. Only two scoring techniques—concentration performance scores and total number of characters canceled—fit the RPCM. The individual items fit the RPCM, with negligible differential item functioning across sex. Graphical model check and likelihood ratio test confirmed the overall fit of the two scoring techniques to RPCM.
American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders. Washington, DC: American Psychiatric Press.
2.
AndersenE. B. (1973) A goodness of fit test for the Rasch model. Psychometrika38: 123–140.
3.
AndrichD. (1978) A rating formulation for ordered response categories. Psychometrika43: 561–573.
4.
Baghaei, P., & Doebler, P. (2018). Introduction to the Rasch Poisson Counts Model: An R tutorial. Psychological Reports. Advanced online publication. doi: 10.1177/0033294118797577.
5.
BaghaeiP.YanagidaT.HeeneM. (2017) Development of a descriptive fit statistic for the Rasch model. North American Journal of Psychology19: 155–168.
6.
BaghaeiP.Tabatabaee-YazdiM. (2016) The logic of latent variable analysis as validity evidence in psychological measurement. The Open Psychology Journal9: 168–175.
7.
Bates, D., Maechler, M., Bolker, B., Walker, S., Christensen, R., Singmann, H., et al. (2017). lme4: Linear mixed-effects models using ‘Eigen' and S4 (R package, version 1.1-14). Retrieved from https://cran.r-project.org/web/packages/lme4/index.html.
8.
BatesM. E.LemayE. P.Jr. (2004) The d2 test of attention: Construct validity and extensions in scoring techniques. Journal of International Neuropsychological Society10: 392–400.
9.
BirnbaumA. (1968) Some latent trait models and their use in inferring an examinee’s ability. In: LordF. M.NovickM. R. (eds) Statistical theories of mental test scores, Reading, MA: Addison-Wesley, pp. 395–479.
BrickenkampR.ZillmerE. (1998) The d2 test of attention, Seattle, WA: Hogrefe & Huber Publishers.
12.
CooleyE. L.MorrisR. D. (1990) Attention in children: A neuropsychologically based model for assessment. Developmental Neuropsychology6: 239–247.
13.
DoeblerA.DoeblerP.HollingH. (2014) A latent ability model for count data and application to processing speed. Applied Psychological Measurement38: 587–598.
14.
DoeblerA.HollingH. (2016) A processing speed test based on rule-based item generation: An analysis with the Rasch Poisson Counts Model. Learning and Individual Differences52: 121–128. doi: 10.1016/j.lindif.2015.01.013.
15.
ForthmannB.GerwigA.HollingH.ÇelikP.StormeM.LubartT. (2016) The be-creative effect in divergent thinking: The interplay of instruction and object frequency. Intelligence57: 25–32.
16.
Fuermaier, A. B. M., Tucha, L., Koerts, J., Aschenbrenner, S., Westermann, C., Weisbrod, M., Lange, K.W., Tucha, O. (2013). Complex prospective memory in adults with attention deficit hyperactivity disorder. PLoS One, 8, e58338. doi:10.1371/journal.pone.0058338.
17.
JansenM. G. H. (1997) Applications of Rasch's Poisson counts model to longitudinal count data. In: LangeheineR.RostJ. (eds) Applications of latent trait and latent class models in the social sciences, Münster, Germany: Waxmann, pp. 380–388.
18.
LeeP.LuW.-S.LiuC.-H.LinH.-Y.HsiehC.-L. (2017) Test–retest reliability and minimal detectable change of the D2 test of attention in patients with schizophrenia. Archives of Clinical Neuropsychology. Advance online publication. doi: 10.1093/arclin/acx123.
19.
ManlyT.AndersonV.Nimmo-SmithI.TurnerA.WatsonP.RobertsonI. H. (2001) The differential assessment of children’s attention: The Test of Everyday Attention for Children (TEA-Ch), normative sample and ADHD performance. Journal of Child Psychology and Psychiatry42: 1065–1081.
20.
MastersG. N. (1982) A Rasch model for partial credit scoring. Psychometrika47: 149–174.
21.
MirskyA. F.AnthonyB. J.DuncanC. C.AhearnM. B.KellamS. G. (1991) Analysis of the elements of attention: A neuropsychological approach. Neuropsychology Review2: 109–145.
22.
Nadri, M. (2018). The Contribution of attention, processing speed, and fluid intelligence to predicting Iranian EFL learners' listening comprehension: Development and validation of two measures of auditory attention. Unpublished master's thesis. Mashhad: Islamic Azad University.
23.
PietersJ. P. M. (1985) Reaction time analysis of simple mental tasks: A general approach. Acta Psychologica59: 227–269.
24.
RaschG. (1980) Probabilistic models for some intelligence and attainment tests (expanded edition), Copenhagen: Danish Institute for Educational Research. (Original work published 1960).
25.
R Development Core Team. (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http: //www.R-project.org/.
26.
ReitanR.WolfsonD. (1985) The Halstead-Reitan neuropsychological battery: Theory and clinical implications, Tucson, Arizona: Neuropsychology Press.
27.
SmithA. (1973) Symbol digit modalities test, Los Angeles, CA: Western Psychological Services.
28.
SohlbergM. M.MateerC. A. (2001) Improving attention and managing attentional problems. Adapting rehabilitation techniques to adults with ADD. Annals of the New York Academy Sciences931: 359–375.
29.
SprayJ. A. (1990) One-parameter item response theory models for psychomotor tests involving repeated independent attempts. Research Quarterly for Exercise and Sport61: 162–168.
30.
SteinbornM. B.LangnerR.FlehmigH. C.HuesteggeL. (2018) Methodology of performance scoring in the d2 sustained-attention test: Cumulative-reliability functions and practical guidelines. Psychological Assessment30: 339–357.
31.
SteinbornM. B.LangnerR.HuesteggeL. (2017) Mobilizing cognition for speeded action: Try-harder instructions promote motivated readiness in the constant-foreperiod paradigm. Psychological Research81: 1135–1151.
32.
StroopJ. (1935) Studies of interference in serial verbal reactions. Journal of Experimental Psychology18: 643–662.
33.
Van BreukelenG. J. P.RoskamE. E. C. I.ElingP. A. T. M.JansenR. W. T. L.SourenD. A. P. B.IckenrothJ. G. M. (1995) A model and diagnostic measures for response-time series on tests of concentration: Historical background, conceptual framework, and some applications. Brain and Cognition27: 147–179.
34.
VerhelstN. D.KamphuisF. H. (2009) A Poisson-gamma model for speed tests. Measurement and Research Department Reports 2009-2, Arnhem, The Netherlands: Cito.
35.
Wechsler, D. (1981). WAIS-R : Wechsler adult intelligence scale-revised. New York, NY: Psychological Corporation.
36.
WrightB. D. (1977) Misunderstanding the Rasch model. Journal of Educational. Measurement14: 219–225.
37.
WrightB. D. (1988) Rasch model derived from Campbell concatenation: Additivity, interval scaling. Rasch Measurement Transactions2: 16Retrieved from https://www.rasch.org/rmt/rmt21b.htm.
38.
WrightB. D. (1989) Dichotomous Rasch model derived from counting right answers: Raw scores as sufficient statistics. Rasch Measurement Transactions3: 62Retrieved from https://www.rasch.org/rmt/rmt32e.htm.
39.
ZillmerE. A.KennedyC. H. (1999) Preliminary United States norms for the d2 test of attention. Archives of Clinical Neuropsychology14: 727–728. doi: 10.1093/arclin/14.8.727.
