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Differential item functioning of the Boston Naming Test in cognitively normal African American and Caucasian older adults

Published online by Cambridge University Press:  01 September 2009

OTTO PEDRAZA ,
NEILL R. GRAFF-RADFORD ,
GLENN E. SMITH ,
ROBERT J. IVNIK ,
FLOYD B. WILLIS ,
RONALD C. PETERSEN  and
JOHN A. LUCAS
OTTO PEDRAZA*
Affiliation:
Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, Florida
NEILL R. GRAFF-RADFORD
Affiliation:
Department of Neurology, Mayo Clinic, Jacksonville, Florida
GLENN E. SMITH
Affiliation:
Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
ROBERT J. IVNIK
Affiliation:
Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
FLOYD B. WILLIS
Affiliation:
Department of Family Medicine, Mayo Clinic, Jacksonville, Florida
RONALD C. PETERSEN
Affiliation:
Department of Neurology, Mayo Clinic, Rochester, Minnesota
JOHN A. LUCAS
Affiliation:
Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, Florida
*
*Correspondence and reprint requests to: Otto Pedraza, Department of Psychiatry and Psychology, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224. E-mail: [email protected]
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Abstract

Scores on the Boston Naming Test (BNT) are frequently lower for African American when compared with Caucasian adults. Although demographically based norms can mitigate the impact of this discrepancy on the likelihood of erroneous diagnostic impressions, a growing consensus suggests that group norms do not sufficiently address or advance our understanding of the underlying psychometric and sociocultural factors that lead to between-group score discrepancies. Using item response theory and methods to detect differential item functioning (DIF), the current investigation moves beyond comparisons of the summed total score to examine whether the conditional probability of responding correctly to individual BNT items differs between African American and Caucasian adults. Participants included 670 adults age 52 and older who took part in Mayo’s Older Americans and Older African Americans Normative Studies. Under a two-parameter logistic item response theory framework and after correction for the false discovery rate, 12 items where shown to demonstrate DIF. Of these 12 items, 6 (“dominoes,” “escalator,” “muzzle,” “latch,” “tripod,” and “palette”) were also identified in additional analyses using hierarchical logistic regression models and represent the strongest evidence for race/ethnicity-based DIF. These findings afford a finer characterization of the psychometric properties of the BNT and expand our understanding of between-group performance. (JINS, 2009, 15, 758–768.)

Keywords

Boston Naming TestItem response theoryDifferential item functioningEthnicityRaceBias
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 15 , Issue 5 , September 2009 , pp. 758 - 768
Copyright
Copyright © The International Neuropsychological Society 2009

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References

REFERENCES

American Education Research Association, American Psychological Association, and the National Council on Measurement in Education. (1999). Standards for educational and psychological testing. Washington, DC: American Education Research Association.Google Scholar
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B, 57, 289–300.Google Scholar
Boomsma, A., & Hoogland, J.J. (2001). The robustness of LISREL modeling revisited. In Cudeck, R., du Toit, S., & Sörbom, D. (Eds.), Structural equation models: Present and future. (pp. 139–168). Lincolnwood, IL: Scientific Software International.Google Scholar
Boone, K.B., Victor, T.L., Wen, J., Razani, J., & Pontón, M. (2007). The association between neuropsychological scores and ethnicity, language, and acculturation variables in a large patient population. Archives of Clinical Neuropsychology, 22, 355–365.CrossRefGoogle Scholar
Brandt, J. (2007). 2005 INS Presidential Address: Neuropsychological crimes and misdemeanors. The Clinical Neuropsychologist, 21, 553–568.Google Scholar
Embretson, S.E., & Reise, S.P. (2000). Item response theory for psychologists. Mahway, NJ: Lawrence Erlbaum Associates.Google Scholar
Ferman, T.J., Ivnik, R.J., & Lucas, J.A. (1998). Boston Naming Test discontinuation rule: Rigorous versus lenient interpretations. Assessment, 5, 13–18.CrossRefGoogle ScholarPubMed
Fillenbaum, G.G., Huber, M., & Taussig, I.M. (1997). Performance of elderly White and African American community residents on the abbreviated CERAD Boston Naming Test. Journal of Clinical & Experimental Neuropsychology, 19, 204–210.Google Scholar
Fillenbaum, G.G., Peterson, B., Welsh-Bohmer, K.A., Kukull, W.A., & Heyman, A. (1998). Progression of Alzheimer’s disease in black and white patients: The CERAD experience, part XVI. Consortium to Establish a Registry for Alzheimer’s Disease. Neurology, 51, 154–158.CrossRefGoogle Scholar
Graves, R.E., Bezeau, S.C., Fogarty, J., & Blair, R. (2004). Boston naming test short forms: A comparison of previous forms with new item response theory based forms. Journal of Clinical and Experimental Neuropsychology, 26, 891–902.Google Scholar
Hambleton, R.K. (2006). Good practices for identifying differential item functioning. Medical Care, 44(Suppl. 3), S182–S188.CrossRefGoogle ScholarPubMed
Hambleton, R.K., & Swaminathan, H. (1985). Item response theory. Principles and applications. Boston: Kluwer-Nijhoff Publishing.Google Scholar
Hambleton, R.K., Swaminathan, H., & Rogers, H.J. (1991). Fundamentals of item response theory. Newbury Park, CA: Sage Publications.Google Scholar
Heaton, R.K., Miller, S.W., Taylor, M.J., & Grant, I. (2004). Revised comprehensive norms for an expanded Halstead-Reitan battery: Demographically-adjusted neuropsychological norms for African American and Caucasian adults. Lutz, FL: Psychological Assessment Resources, Inc.Google Scholar
Holman, R., Glas, C.A., & de Haan, R.J. (2003). Power analysis in randomized clinical trials based on item response theory. Controlled Clinical Trials, 24, 390–410.Google Scholar
Inouye, S.K., Albert, M.S., Mohs, R., Sun, K., & Berkman, L.F. (1993). Cognitive performance in a high functioning community dwelling elderly population. Journal of Gerontology: Medical Sciences, 48, M146–M151.CrossRefGoogle Scholar
Ivnik, R.J., Malec, J.F., Tangalos, E.G., Petersen, R.C., Kokmen, E., & Kurland, L.T. (1990). The Auditory Verbal Learning Test (AVLT): Norms of ages 55 and older. Psychological Assessment, 2, 304–312.CrossRefGoogle Scholar
Jodoin, M.G., & Gierl, M.J. (2001). Evaluating Type I error and power rates using an effect size measure with the logistic regression procedure for DIF detection. Applied Measurement in Education, 14, 329–349.CrossRefGoogle Scholar
Jöreskog, K.G., & Sörbom, D. (2006). LISREL 8.80. Chicago, IL: Scientific Software International.Google Scholar
Jöreskog, K.G., & Sörbom, D. (1997). LISREL 8: User’s reference guide (2nd ed.). Chicago, IL: Scientific Software International.Google Scholar
Kaplan, E., Goodglass, H., & Weintraub, S. (1983). The Boston Naming Test. Philadelphia: Lea & Febiger.Google Scholar
Lichtenberg, P.A., Ross, T., & Christensen, B. (1994). Preliminary normative data on the Boston Naming Test for an older urban population. Clinical Neuropsychologist, 8, 109–111.Google Scholar
Lucas, J.A., Ivnik, R.J., Willis, F.B., Ferman, T.J., Smith, G.E., Parfitt, F.C., et al. . (2005a). Mayo’s Older African American Normative Studies: Normative data for commonly used clinical neuropsychological measures. The Clinical Neuropsychologist, 19, 162–183.CrossRefGoogle ScholarPubMed
Lucas, J.A., Ivnik, R.J., Smith, G.E., Ferman, T.J., Willis, F.B., Petersen, R.C., et al. . (2005b). Mayo’s Older African American Normative Studies: Norms for Boston Naming Test, Controlled Oral Word Association, Category Fluency, Animal Naming, Token Test, WRAT-3 Reading, Trail Making Test, Stroop Test, and Judgment of Line Orientation. The Clinical Neuropsychologist, 19, 243–269.Google Scholar
Manly, J.J. (2005). Advantages and disadvantages of separate norms for African Americans. Clinical Neuropsychologist, 19, 270–275.Google Scholar
Manly, J.J., Byrd, D.A., Touradji, P., & Stern, Y. (2004). Acculturation, reading level, and neuropsychological test performance among African American elders. Applied Neuropsychology, 11, 37–46.Google Scholar
Manly, J.J., Jacobs, D.M., Sano, M., Bell, K., Merchant, C.A., Small, S.A., & Stern, Y. (1998). Cognitive test performance among nondemented elderly African Americans and whites. Neurology, 50(5), 1238–1245.CrossRefGoogle ScholarPubMed
Manly, J.J.Jacobs, D.M., Touradji, P., Small, S.A., & Stern, Y. (2002). Reading level attenuates differences in neuropsychological test performance between African American and White elders. Journal of the International Neuropsychological Society, 8, 341–348.CrossRefGoogle ScholarPubMed
Miles, G.T. (2002). Neuropsychological assessment of African Americans. In Ferraro, F.R. (Ed.), Studies on neuropsychology, development, and cognition (pp. 63–77). Lisse, Netherlands: Swets & Zeitlinger Publishers.Google Scholar
Nandakumar, R., & Stout, W. (1993). Refinements of Stout’s procedure for assessing latent trait unidimensionality. Journal of Educational Statistics, 18, 41–68.Google Scholar
Orlando-Edelen, M.O., Thissen, D., Teresi, J.A., Kleinman, M., & Ocepek-Welikson, K. (2006). Identification of differential item functioning using item response theory and the likelihood-based model comparison approach: Application to the Mini-Mental State Examination. Medical Care, 44(Suppl. 3), S134–S142.Google Scholar
Pedraza, O., & Mungas, D. (2008). Measurement in cross-cultural neuropsychology. Neuropsychology Review, 18, 184–193.CrossRefGoogle ScholarPubMed
Smith, G.E., Ivnik, R.J., & Lucas, J.A. (2008). Assessment techniques: Tests, test batteries, norms, and methodological approaches. In Morgan, J. & Ricker, J. (Eds.), Textbook of clinical neuropsychology (pp. 38–57). New York: Taylor & Francis Group.Google Scholar
Stout, W. (1987). A nonparametric approach for assessing latent trait unidimensionality. Psychometrika, 52, 589–617.Google Scholar
Stout, W., Froelich, A., & Gao, F. (2001). Using resampling methods to produce an improved DIMTEST procedure. In Boomsma, A., van Duijn, M.A.J., & Snijders, T.A.B (Eds.), Essays on item response theory (pp. 357–376). New York: Springer-Verlag.Google Scholar
Swaminathan, H., & Rogers, H.J. (1990). Detecting differential item functioning using logistic regression procedures. Journal of Educational Measurement, 26, 361–270.Google Scholar
Teresi, J.A. (2006). Different approaches to differential item functioning in health applications: Advantages, disadvantages and some neglected topics. Medical Care, 44(Suppl. 3), S152–S170.Google Scholar
Teresi, J.A., Kleinman, M., & Ocepek-Welikson, K. (2000). Modern psychometric methods for detection of differential item functioning: Application to cognitive assessment measures. Statistics in Medicine, 19, 1651–1683.Google Scholar
Teresi, J.A., Ocepek-Welikson, K., Kleinman, M., Cook, K.F., Crane, P.K., Gibbons, L.E., et al. . (2007). Evaluating measurement equivalence using the item response theory log-likelihood ration (IRTLR) method to assess differential item functioning (DIF): Applications (with illustrations) to measures of physical functioning ability and general distress. Quality of Life Research, 16(Suppl. 1), 43–68.CrossRefGoogle Scholar
Thissen, D. (2001). IRTLRDIF v2.0b: Software for the computation of the statistics involved in item response theory likelihood-ratio tests for differential item functioning. University of North Carolina at Chapel Hill: L.L. Thurstone Psychometric Laboratory.Google Scholar
Thissen, D. (2003). MULTILOG 7.0: Multiple, categorical item analysis and test scoring using item response theory. Chicago: Scientific Software International.Google Scholar
Thissen, D., Steinberg, L., & Kuang, D. (2002). Quick and easy implementation of the Benjamini-Hochberg procedure for controlling the false positive rate in multiple comparisons. Journal of Educational and Behavioral Statistics, 27, 77–83.Google Scholar
Wagner, M.T., Wymer, J.H., Carlozzi, N.E., Bachman, D., Walker, A., & Mintzer, J. (2007). Alzheimer Study Group. Preliminary examination of progression of Alzheimer’s disease in a rural Southern African American cohort. Archives of Clinical Neuropsychology, 22, 405–414.Google Scholar
Welsh, K., Fillenbaum, G., Wilkinson, W., Heyman, A., Mohs, R.C., Stern, Y., et al. . (1995). Neuropsychological test performance in African American and White patients with Alzheimer’s disease. Neurology, 45, 2207–2211.Google Scholar
Whitfield, K.E., Fillenbaum, G.G., Pieper, C., Albert, M.S., Berkman, L.F., Blazer, D.G., et al. . (2000). The effect of race and health-related factors on naming and memory. The MacArthur Studies of Successful Aging. Journal of Aging & Health, 12, 69–89.Google Scholar
Zumbo, B.D. (1999). A handbook on the theory and methods of differential item functioning (DIF): Logistic regression modeling as a unitary framework for binary and Likert-type (ordinal) item scores. Directorate of Human Resources Research and Evaluation, Department of National Defense: Ottawa, Canada. Retrieved June 8, 2005 from http://educ.ubc.ca/faculty/zumbo/DIF/index.htmlGoogle Scholar