References
- Aita, S. L. (2020). Neuropsychological intra-individual variability: Review and meta-analysis in clinical adult samples [Doctoral dissertation], University of South Alabama.
- Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., Snyder, P. J., Carrillo, M. C., Thies, B., & Phelps, C. H. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the national institute on aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 270–279. https://doi.org/https://doi.org/10.1016/j.jalz.2011.03.008
- Allen, M., Poggiali, D., Whitaker, K., Marshall, T. R., Van Langen, J., & Kievit, R. A. (2021). Raincloud plots: A multi-platform tool for robust data visualization. Wellcome Open Research, 4(63), 63. https://doi.org/https://doi.org/10.12688/wellcomeopenres.15191.2
- Anderson, E. D., Wahoske, M., Huber, M., Norton, D., Li, Z., Koscik, R. L., Umucu, E., Johnson, S. C., Jones, J., Asthana, S., & Gleason, C. E., & Alzheimer’s Disease Neuroimaging Initiative. (2016). Cognitive variability—A marker for incident MCI and AD: An analysis for the Alzheimer’s disease neuroimaging initiative. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 4(1), 47–55. https://doi.org/http://doi.org/10.1016/j.dadm.2016.05.0032352-8729/.
- Anderson, N. D. (2019). State of the science on mild cognitive impairment (MCI). CNS Spectrums, 24(1), 78–87. https://doi.org/https://doi.org/10.1017/S1092852918001347
- Anderson, N. D., Ebert, P. L., Jennings, J. M., Grady, C. L., Cabeza, R., & Graham, S. J. (2008). Recollection- and familiarity-based memory in healthy aging and amnestic mild cognitive impairment. Neuropsychology, 22(2), 177–187. https://doi.org/https://doi.org/10.1037/0894-4105.22.2.177
- Army Individual Test Battery. (1944). Manual of Directions and Scoring. Washington, DC: War Department, Adjutant General’s Office.
- Bauer, R. M., Iverson, G. L., Cernich, A. N., Binder, L. M., Ruff, R. M., & Naugle, R. I. (2012). Computerized neuropsychological assessment devices: Joint position paper of the American Academy of Clinical Neuropsychology and the National Academy of Neuropsychology. Archives of Clinical Neuropsychology, 27(3), 362–373. https://doi.org/https://doi.org/10.1093/arclin/acs027
- Belleville, S., Chertkow, H., & Gauthier, S. (2007). Working memory and control of attention in persons with Alzheimer’s disease and mild cognitive impairment. Neuropsychology, 21(4), 458–469. https://doi.org/https://doi.org/10.1037/0894-4105.21.4.458
- Belleville, S., Fouquet, C., Hudon, C., Zomahoun, H. T. V., & Croteau, J. (2017). Neuropsychological measures that predict progression from mild cognitive impairment to Alzheimer's type dementia in older adults: a systematic review and meta-analysis. Neuropsychology Review,27(4), 328–353. https://doi.org/https://doi.org/10.1007/s11065-017-9361-5
- Bennett, I. J., Golob, E. J., Parker, E. S., & Starr, A. (2006). Memory evaluation in mild cognitive impairment using recall and recognition tests. Journal of Clinical and Experimental Neuropsychology, 28(8), 1408–1422. https://doi.org/https://doi.org/10.1080/13803390500409583
- Bielak, A. A. M., Hultsch, D. F., Strauss, E., MacDonald, S. W. S., & Hunter, M. A. (2010). Intraindividual variability in reaction time predicts cognitive outcomes 5 years later. Neuropsychology, 24(6), 731–741. https://doi.org/https://doi.org/10.1037/a0019802
- Brandt, J., Aretouli, E., Neijstrom, E., Samek, J., Manning, K., Albert, M. S., & Bandeen-Roche, K. (2009). Selectivity of executive function deficits in mild cognitive impairment. Neuropsychology, 23(5), 607–618. https://doi.org/https://doi.org/10.1037/a0015851
- Brewster, P., Tuokko, H., & MacDonald, S. (2012). Inter-test variability contributes independently to the five-year prediction of Alzheimer’s disease in nondemented older adults. Alzheimer’s & Dementia, 4(8), P369. doi:https://doi.org/10.1016/j.jalz.2012.05.1010.
- Chetverikov, A., & Upravitelev, P. (2016). Online versus offline: The web as a medium for response time data collection. Behavior Research Methods, 48(3), 1086–1099. https://doi.org/https://doi.org/10.3758/s13428-015-0632-x
- Chow, R., Rabi, R., Paracha, S., Vasquez, B. P., Hasher, L., Alain, C., & Anderson, N. D. (2021). Reaction time intra-individual variability reveals inhibitory deficits in single- and multiple-domain amnestic mild cognitive impairment. The Journals of Gerontology: Series B, gbab051. https://doi.org/https://doi.org/10.1093/geronb/gbab051.
- Christensen, H., Dear, K. B. G., Anstey, K. J., Parslow, R. A., Sachdev, P., & Jorm, A. F. (2005). Within-occasion intraindividual variability and preclinical diagnostic status: Is intraindividual variability an indicator of mild cognitive impairment? Neuropsychology, 19(3), 309–317. https://doi.org/https://doi.org/10.1037/0894-4105.19.3.309
- Clark, L. R., Schiehser, D. M., Weissberger, G. H., Salmon, D. P., Delis, D. C., & Bondi, M. W. (2012). Specific measures of executive function predict cognitive decline in older adults. Journal of the International Neuropsychological Society, 18(1), 118–127. https://doi.org/https://doi.org/10.1017/S1355617711001524
- Cloutier, S., Chertkow, H., Kergoat, M.-J., Gauthier, S., & Belleville, S. (2015). Patterns of cognitive decline prior to dementia in persons with mild cognitive impairment. Journal of Alzheimer’s Disease, 47(4), 901–913. https://doi.org/https://doi.org/10.3233/JAD-142910
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.
- Costa, A. S., Dogan, I., Schulz, J. B., & Reetz, K. (2019). Going beyond the mean: Intraindividual variability of cognitive performance in prodromal and early neurodegenerative disorders. The Clinical Neuropsychologist, 33(2), 369–389. https://doi.org/https://doi.org/10.1080/13854046.2018.1533587
- Cribbie, R. A. (2017). Multiplicity control, school uniforms, and other perplexing debates. Canadian Journal of Behavioural Science/Revue Canadienne des Sciences du Comportement, 49(3), 159–165. https://doi.org/https://doi.org/10.1037/cbs0000075
- Crump, M. J., McDonnell, J. V., Gureckis, T. M., & Gilbert, S. (2013). Evaluating Amazon’s mechanical turk as a tool for experimental behavioral research. PLoS ONE, 8(3), e57410. https://doi.org/https://doi.org/10.1371/journal.pone.0057410
- Damian, M., Hausner, L., Jekel, K., Richter, M., Froelich, L., Almkvist, O., Boada, M., Bullock, R., De Deyn, P. P., Frisoni, G. B., Hampel, H., Jones, R. W., Kehoe, P., Lenoir, H., Minthon, L., Olde Rikkert, M. G. M., Rodriguez, G., Scheltens, P., Soininen, H., Spiru, L., … Visser, P. J. (2013). Single-domain amnestic mild cognitive impairment identified by cluster analysis predicts Alzheimer’s disease in the European prospective DESCRIPA study. Dementia and Geriatric Cognitive Disorders, 36(1–2), 1–19. https://doi.org/https://doi.org/10.1159/000348354
- De Leeuw, J. R., & Motz, B. A. (2016). Psychophysics in a web browser? Comparing response times collected with JavaScript and psychophysics toolbox in a visual search task. Behavior Research Methods, 48(1), 1–12. https://doi.org/https://doi.org/10.3758/s13428-015-0567-2
- Delis, D., Kaplan, E., & Kramer, J. (2001). Delis-Kaplan executive function system: Technical manual. Harcourt Assessment Company.
- Dixon, R. A., Garrett, D. D., Lentz, T. L., MacDonald, S. W. S., Strauss, E., & Hultsch, D. F. (2007). Neurocognitive markers of cognitive impairment: Exploring the roles of speed and inconsistency. Neuropsychology, 21(3), 381–399. https://doi.org/https://doi.org/10.1037/0894-4105.21.3.381
- Duchek, J. M., Balota, D. A., Tse, C.-S., Holtzman, D. M., Fagan, A. M., & Goate, A. M. (2009). The utility of intraindividual variability in selective attention tasks as an early marker for Alzheimer’s disease. Neuropsychology,23(6), 746–758. https://doi.org/https://doi.org/10.1037/a0016583
- Dudas, R. B., Clague, F., Thompson, S. A., Graham, K. S., & Hodges, J. R. (2005). Episodic and semantic memory in mild cognitive impairment. Neuropsychologia, 43(9), 1266–1276. https://doi.org/https://doi.org/10.1016/j.neuropsychologia.2004.12.005
- Enochson, K., & Culbertson, J. (2015). Collecting psycholinguistic response time data using Amazon Mechanical Turk. PLoS One,10(3), e0116946. https://doi.org/https://doi.org/10.1371/journal.pone.0116946
- Feenstra, H. E. M., Vermeulen, I. E., Murre, J. M. J., & Schagen, S. B. (2017). Online cognition: Factors facilitating reliable online neuropsychological test results. The Clinical Neuropsychologist, 31(1), 59–84. https://doi.org/https://doi.org/10.1080/13854046.2016.1190405
- Fray, P. J., Robbins, T. W., & Sahakian, B. J. (1996). Neuropsychiatric applications of CANTAB. International Journal of Geriatric Psychiatry, 11(4), 329–336. https://doi.org/https://doi.org/10.1002/(SICI)1099-1166(199604)11:4<329::AID-GPS453>3.0.CO;2-6
- Freitas, S., Simões, M. R., Alves, L., & Santana, I. (2013). Montreal cognitive assessment. Alzheimer Disease & Associated Disorders, 27(1), 37–43. https://doi.org/https://doi.org/10.1097/WAD.0b013e3182420bfe
- Ganguli, M., Snitz, B. E., Saxton, J. A., Chang, -C.-C. H., Lee, C.-W., Vander Bilt, J., Hughes, T. F., Loewenstein, D. A., Unverzagt, F. W., & Petersen, R. C. (2011). Outcomes of mild cognitive impairment by definition: A population study. Archives of Neurology, 68(6), 761–767. https://doi.org/https://doi.org/10.1001/archneurol.2011.101
- Germine, L., Reinecke, K., & Chaytor, N. S. (2019). Digital neuropsychology: Challenges and opportunities at the intersection of science and software. The Clinical Neuropsychologist, 33(2), 271–286. https://doi.org/https://doi.org/10.1080/13854046.2018.1535662
- Gershon, R. C., Wagster, M. V., Hendrie, H. C., Fox, N. A., Cook, K. F., & Nowinski, C. J. (2013). NIH toolbox for assessment of neurological and behavioral function. The Lancet Neurology, 80(11 Suppl 3), S2–S6. https://doi.org/https://doi.org/10.1212/WNL.0b013e3182872e5f
- Gleason, C. E., Norton, D., Anderson, E. D., Wahoske, M., Washington, D. T., Umucu, E., Koscik, R. L., Dowling, N. M., Johnson, S. C., Carlsson, C. M., & Asthana, S. (2018). Cognitive variability predicts incident Alzheimer’s disease and mild cognitive impairment comparable to a cerebrospinal fluid biomarker. Journal of Alzheimer’s Disease, 61(1), 79–89. https://doi.org/https://doi.org/10.3233/JAD-170498
- Gorus, E., De Raedt, R., Lambert, M., Lemper, J.-C., & Mets, T. (2008). Reaction times and performance variability in normal aging, mild cognitive impairment, and Alzheimer’s disease. Journal of Geriatric Psychiatry and Neurology, 21(3), 204–218. https://doi.org/https://doi.org/10.1177/0891988708320973
- Gravetter, F. J., & Wallnau, L. B. (2009). Statistics for the behavioural sciences (8th ed.). Wadsworth CENGAGE Learning: Belmont, CA.
- Halliday, D. W. R., Stawski, R. S., Cerino, E. S., DeCarlo, C. A., Grewal, K., & MacDonald, S. W. S. (2018). Intraindividual variability across neuropsychological tests: Dispersion and disengaged lifestyle increase risk for Alzheimer’s disease. Journal of Intelligence, 6(1), E12. https://doi.org/https://doi.org/10.3390/jintelligence6010012
- Haynes, B. I., Bauermeister, S., & Bunce, D. (2017). A systematic review of longitudinal associations between reaction time intraindividual variability and age-related cognitive decline or impairment, dementia, and mortality. Journal of the International Neuropsychological Society, 23(5), 431–445. https://doi.org/https://doi.org/10.1017/S1355617717000236
- Hilbig, B. E. (2016). Reaction time effects in lab-versus web-based research: Experimental evidence. Behavior Research Methods, 48(4), 1718–1724. https://doi.org/https://doi.org/10.3758/s13428-015-0678-9
- Hilborn, J. V., Strauss, E., Hultsch, D. F., & Hunter, M. A. (2009). Intraindividual variability across cognitive domains: investigation of dispersion levels and performance profiles in older adults. Journal of clinical and experimental neuropsychology,31(4), 412–424. https://doi.org/https://doi.org/10.1080/13803390802232659
- Holtzer, R. (2008). Within-person across-neuropsychological test variability and incident dementia. JAMA, 300(7), 823–830. https://doi.org/https://doi.org/10.1001/jama.300.7.823
- Hultsch, D. F., MacDonald, S. W. S., & Dixon, R. A. (2002). Variability in reaction time performance of younger and older adults. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 57(2), PP101–P115. https://doi.org/https://doi.org/10.1093/geronb/57.2.P101
- Hultsch, D. F., MacDonald, S. W. S., Hunter, M. A., Levy-Bencheton, J., & Strauss, E. (2000). Intraindividual variability in cognitive performance in older adults: Comparison of adults with mild dementia, adults with arthritis, and healthy adults. Neuropsychology, 14(4), 588–598.
- Irish, M., Lawlor, B. A., Coen, R. F., & O’Mara, S. M. (2011). Everyday episodic memory in amnestic mild cognitive impairment: A preliminary investigation. BMC Neuroscience, 12(1), 80. https://doi.org/https://doi.org/10.1186/1471-2202-12-80
- Iverson, G. L., Brooks, B. L., Ashton, V. L., Johnson, L. G., & Gualtieri, C. T. (2009). Does familiarity with computers affect computerized neuropsychological test performance? Journal of Clinical and Experimental Neuropsychology, 31(5), 594–604. https://doi.org/https://doi.org/10.1080/13803390802372125
- Jack, C. R., Jr., Knopman, D. S., Jagust, W. J., Petersen, R. C., Weiner, M. W., Aisen, P. S., Shaw, L. M., Vemuri, P., Wiste, H. J., Weigand, S. D., Lesnick, T. G., Pankratz, V. S., Donohue, M. C., & Trojanowski, J. Q. (2013). Tracking pathophysiological processes in Alzheimer’s disease: An updated hypothetical model of dynamic biomarkers. The Lancet Neurology, 12(2), 207–216. https://doi.org/https://doi.org/10.1016/S1474-4422(12)70291-0
- Jak, A. J., Bondi, M. W., Delano-Wood, L., Wierenga, C., Corey-Bloom, J., Salmon, D. P., & Delis, D. C. (2009). Quantification of five neuropsychological approaches to defining mild cognitive impairment. The American Journal of Geriatric Psychiatry, 17(5), 368–375. https://doi.org/https://doi.org/10.1097/JGP.0b013e31819431d5
- Kälin, A. M., Pflüger, M., Gietl, A. F., Riese, F., Jäncke, L., Nitsch, R. M., & Hock, C. (2014). Intraindividual variability across cognitive tasks as a potential marker for prodromal Alzheimer’s disease. Frontiers in Aging Neuroscience, 6, 147. https://doi.org/https://doi.org/10.3389/fnagi.2014.00147
- Kaplan, E., Goodglas, H., & Weintraub, S. (2001). The Boston naming test-2 (2nd ed.). Pro-Ed.
- Kay, C. D., Seidenberg, M., Durgerian, S., Nielson, K. A., Smith, J. C., Woodard, J. L., & Rao, S. M. (2017). Motor timing intraindividual variability in amnestic mild cognitive impairment and cognitively intact elders at genetic risk for Alzheimer’s disease. Journal of Clinical and Experimental Neuropsychology, 39(9), 866–875. https://doi.org/https://doi.org/10.1080/13803395.2016.1273321
- Kochan, N. A., Bunce, D., Pont, S., Crawford, J. D., Brodaty, H., & Sachdev, P. S. (2016). Reaction time measures predict incident dementia in community-living older adults: The Sydney memory and ageing study. The American Journal of Geriatric Psychiatry, 24(3), 221–231. https://doi.org/https://doi.org/10.1016/j.jagp.2015.12.005.
- Koen, J. D., & Yonelinas, A. P. (2014). The effects of healthy aging, amnestic mild cognitive impairment, and Alzheimer’s disease on recollection and familiarity: A meta-analytic review. Neuropsychology Review, 24(3), 332–354. https://doi.org/https://doi.org/10.1007/s11065-014-9266-5
- Koscik, R. L., Berman, S. E., Clark, L. R., Mueller, K. D., Okonkwo, O. C., Gleason, C. E., Hermann, B. P., Sager, M. A., & Johnson, S. C. (2016). Intraindividual cognitive variability in middle age predicts cognitive impairment 8–10 years later: Results from the Wisconsin registry for Alzheimer’s prevention. Journal of the International Neuropsychological Society, 22(10), 1016–1025. https://doi.org/https://doi.org/10.1017/S135561771600093X
- LaPlume, A. A., Anderson, N. D., McKetton, L., Levine, B., & Troyer, A. K. (2021). When I’m 64: Age -related variability in over 40,000 online cognitive test takers. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences. Advance online publication. https://doi.org/https://doi.org/10.1093/geronb/gbab143
- Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. The Gerontologist, 9(3 Part 1), 179–186. https://doi.org/https://doi.org/10.1093/geront/9.3_Part_1.179
- Leach, L., Kaplan, E., Rewilak, D., Richards, B., & Proulx, G. (2000). Kaplan Baycrest neurocognitive assessment manual. The Psychological Corporation.
- Libon, D. J., Xie, S. X., Eppig, J., Wicas, G., Lamar, M., Lippa, C., Bettcher, B. M., Price, C. C., Giovannetti, T., Swenson, R., & Wambach, D. M. (2010). The heterogeneity of mild cognitive impairment: A neuropsychological analysis. Journal of the International Neuropsychological Society, 16(1), 84–93. https://doi.org/https://doi.org/10.1017/S1355617709990993
- Lu, H., & Lam, L. C. W. (2017). Impacts of ‘two-level’ variability on the differential power for montreal cognitive assessment (MoCA) in prodromal dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 88(2), 186–187. https://doi.org/https://doi.org/10.1136/jnnp-2016-314435
- MacDonald, S., Brewster, P., Laukka, E., Fratiglioni, L., & Bäckman, L. (2012). Intraindividual variability across neuropsychological tasks is associated with risk of Alzheimer’s disease. Alzheimer’s & Dementia, 4(8), P370. https://doi.org/https://doi.org/10.1016/j.jalz.2012.05.1016
- Malek-Ahmadi, M., Lu, S., Chan, Y., Perez, S. E., Chen, K., Mufson, E. J., & Pahan, K. (2017). Cognitive domain dispersion association with Alzheimer’s disease pathology. Journal of Alzheimer’s Disease, 58(2), 575–583. https://doi.org/https://doi.org/10.3233/JAD-161233
- McLaughlin, P. M., Borrie, M. J., & Murtha, S. J. E. (2010). Shifting efficacy, distribution of attention and controlled processing in two subtypes of mild cognitive impairment: Response time performance and intra-individual variability on a visual search task. Neurocase, 16(5), 408–417. https://doi.org/https://doi.org/10.1080/13554791003620306
- Miller, J. B., & Barr, W. B. (2017). The technology crisis in neuropsychology. Archives of Clinical Neuropsychology, 32(5), 541–554. https://doi.org/https://doi.org/10.1093/arclin/acx050
- Mitchell, J., Arnold, R., Dawson, K., Nestor, P. J., & Hodges, J. R. (2009). Outcome in subgroups of mild cognitive impairment (MCI) is highly predictable using a simple algorithm. Journal of Neurology, 256(9), 1500–1509. https://doi.org/https://doi.org/10.1007/s00415-009-5152-0
- Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005). The montreal cognitive assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. https://doi.org/https://doi.org/10.1111/j.1532-5415.2005.53221.x
- Ownby, R. L., Loewenstein, D. A., Schram, L., & Acevedo, A. (2004). Assessing the cognitive abilities that differentiate patients with Alzheimer's disease from normals: single and multiple factor models. International Journal of Geriatric Psychiatry,19(3), 232–242. https://doi.org/https://doi.org/10.1002/gps.1056
- Palmer, K., Fratiglioni, L., & Winblad, B. (2003). What is mild cognitive impairment? Variations in definitions and evolution of nondemented persons with cognitive impairment. Acta Neurologica Scandinavica,107(179), 14–20. https://doi.org/https://doi.org/10.1034/j.1600-0404.107.s179.2.x
- Parsons, T. D., McMahan, T., & Kane, R. (2018). Practice parameters facilitating adoption of advanced technologies for enhancing neuropsychological assessment paradigms. The Clinical Neuropsychologist, 32(1), 16–41. https://doi.org/https://doi.org/10.1080/13854046.2017.1337932
- Paterson, T., Sivajohan, B., Gardner, S., Binns, M. A., Stokes, K. A., Freedman, M., Levine, B., Troyer, A. K., & Gutchess, A. (2021). Accuracy of a self-administered online cognitive assessment in detecting amnestic mild cognitive impairment. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, gbab097. https://doi.org/https://doi.org/10.1093/geronb/gbab097
- Petersen, R. C. (Ed.). (2003). Mild cognitive impairment: Aging to Alzheimer’s disease. Oxford University Press.
- Petersen, R. C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256(3), 183–194. https://doi.org/https://doi.org/10.1111/j.1365-2796.2004.01388.x
- Petersen, R. C., Doody, R., Kurz, A., Mohs, R. C., Morris, J. C., Rabins, P. V., Ritchie, K., Rossor, M., Thal, L., & Winblad, B. (2001). Current concepts in mild cognitive impairment. Archives of Neurology, 58(12), 1985–1992. https://doi.org/https://doi.org/10.1001/archneur.58.12.1985
- Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56(3), 303–308. https://doi.org/https://doi.org/10.1001/archneur.56.3.303
- Phillips, M., Rogers, P., Haworth, J., Bayer, A., Tales, A., & Rypma, B. (2013). Intra-individual reaction time variability in mild cognitive impairment and Alzheimer’s disease: Gender, processing load and speed factors. PloS One, 8(6), e65712. https://doi.org/https://doi.org/10.1371/journal.pone.0065712
- R Core Team. (2020). R:A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/
- Rabi, R., Vasquez, B. P., Alain, C., Hasher, L., Belleville, S., & Anderson, N. D. (2020). Inhibitory control deficits in individuals with amnestic mild cognitive impairment: A meta-analysis. Neuropsychology Review, 30(1), 97–125. https://doi.org/https://doi.org/10.1007/s11065-020-09428-6
- Ramratan, W. S., Rabin, L. A., Wang, C., Zimmerman, M. E., Katz, M. J., Lipton, R. B., & Buschke, H. (2012). Level of recall, retrieval speed, and variability on the cued-recall retrieval speed task (CRRST) in individuals with amnestic mild cognitive impairment. Journal of the International Neuropsychological Society: JINS, 18(2), 260–268. https://doi.org/https://doi.org/10.1017/S1355617711001664
- Reimers, S., & Stewart, N. (2007). Adobe flash as a medium for online experimentation: A test of reaction time measurement capabilities. Behavior Research Methods, 39(3), 365–370. https://doi.org/https://doi.org/10.3758/BF03193004
- Reimers, S., & Stewart, N. (2015). Presentation and response timing accuracy in Adobe Flash and HTML5/JavaScript web experiments. Behavior Research Methods, 47(2), 309–327. https://doi.org/https://doi.org/10.3758/s13428-014-0471-1
- Roalf, D. R., Quarmley, M., Mechanic-Hamilton, D., Wolk, D. A., Arnold, S. E., & Moberg, P. J. (2016). Within-individual variability: An index for subtle change in neurocognition in mild cognitive impairment. Journal of Alzheimer’s Disease, 54(1), 325–335. https://doi.org/https://doi.org/10.3233/JAD-160259
- Roberts, R. O., Knopman, D. S., Mielke, M. M., Cha, R. H., Pankratz, V. S., Christianson, T. J. H., Geda, Y. E., Boeve, B. F., Ivnik, R. J., Tangalos, E. G., Rocca, W. A., & Petersen, R. C. (2014). Higher risk of progression to dementia in mild cognitive impairment cases who revert to normal. Neurology, 82(4), 317–325. https://doi.org/https://doi.org/10.1212/WNL.0000000000000055
- Sachdev, P. S., Lipnicki, D. M., Crawford, J., Reppermund, S., Kochan, N. A., Trollor, J. N., Wen, W., Draper, B., Slavin, M. J., Kang, K., Lux, O., Mather, K. A., Brodaty, H., & Team, A. S., & The Sydney Memory Ageing Study Team. (2013). Factors predicting reversion from mild cognitive impairment to normal cognitive functioning: A population-based study. PloS One, 8(3), e59649. https://doi.org/https://doi.org/10.1371/journal.pone.0059649
- Saunders, N. L. J., & Summers, M. J. (2011). Longitudinal deficits to attention, executive, and working memory in subtypes of mild cognitive impairment. Neuropsychology, 25(2), 237–248. https://doi.org/https://doi.org/10.1037/a0021134
- Schneider, J. A., Arvanitakis, Z., Leurgans, S. E., & Bennett, D. A. (2009). The neuropathology of probable Alzheimer disease and mild cognitive impairment. Annals of Neurology: Official Journal of the American Neurological Association and the Child Neurology Society, 66(2), 200–208. https://doi.org/https://doi.org/10.1002/ana.21706
- Serra, L., Bozzali, M., Cercignani, M., Perri, R., Fadda, L., Caltagirone, C., & Carlesimo, G. A. (2010). Recollection and familiarity in amnesic mild cognitive impairment. Neuropsychology, 24(3), 316–326. https://doi.org/https://doi.org/10.1037/a0017654
- Serrano-Pozo, A., Frosch, M. P., Masliah, E., & Hyman, B. T. (2011). Neuropathological alterations in Alzheimer disease. Cold Spring Harbor Perspectives in Medicine, 1(1), a006189. https://doi.org/https://doi.org/10.1101/cshperspect.a006189
- Slote, J., & Strand, J. F. (2016). Conducting spoken word recognition research online: Validation and a new timing method. Behavior Research Methods, 48(2), 553–566. https://doi.org/https://doi.org/10.3758/s13428-015-0599-7
- Strauss, E., MacDonald, S. W. S., Hunter, M. A., Moll, A., & Hultsch, D. F. (2002). Intraindividual variability in cognitive performance in three groups of older adults: Cross-domain links to physical status and self-perceived affect and beliefs. Journal of the International Neurological Society, 8(7), 893–906. doi:https://doi.org/10.1017/s1355617702870035.
- Stuss, D. T., Murphy, K. J., Binns, M. A., & Alexander, M. P. (2003). Staying on the job: The frontal lobes control individual performance variability. Brain, 126(11), 2363–2380. https://doi.org/https://doi.org/10.1093/brain/awg237
- Tabert, M. H., Manly, J. J., Liu, X., Pelton, G. H., Rosenblum, S., Jacobs, M., Zamora, D., Goodkind, M., Bell, K., Stern, Y., & Devanand, D. P. (2006). Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment. Archives of General Psychiatry, 63(8), 916–924. https://doi.org/https://doi.org/10.1001/archpsyc.63.8.916
- Tales, A., Leonards, U., Bompas, A., Snowden, R. J., Philips, M., Porter, G., Haworth, J., Wilcock, G., & Bayer, A. (2012). Intra-individual reaction time variability in amnestic mild cognitive impairment: A precursor to dementia? Journal of Alzheimer’s Disease, 32(2), 457–466. https://doi.org/https://doi.org/10.3233/JAD-2012-120505
- Tarnanas, I., Papagiannopoulos, S., Kazis, D., Wiederhold, M., Widerhold, B., & Tsolaki, M. (2015). Reliability of a novel serious game using dual-task gait profiles to early characterize aMCI. Frontiers in Aging Neuroscience, 7, 1–15. https://doi.org/https://doi.org/10.3389/fnagi.2015.00050
- Traykov, L., Raoux, N., Latour, F., Gallo, L., Hanon, O., Baudic, S., Bayle, C., Wenisch, E., Remy, P., & Rigaud, A.-S. (2007). Executive functions deficit in mild cognitive impairment. Cognitive and Behavioral Neurology, 20(4), 219–224. https://doi.org/https://doi.org/10.1097/WNN.0b013e31815e6254
- Troyer, A. K., Murphy, K. J., Anderson, N. D., Craik, F. I. M., Moscovitch, M., Maione, A., & Gao, F. (2012). Associative recognition in mild cognitive impairment: Relationship to hippocampal volume and apolipoprotein E. Neuropsychologia, 50(14), 3721–3728. https://doi.org/https://doi.org/10.1016/j.neuropsychologia.2012.10.018
- Troyer, A. K., Murphy, K. J., Anderson, N. D., Hayman-Abello, B. A., Craik, F. I. M., & Moscovitch, M. (2008). Item and associative memory in amnestic mild cognitive impairment: Performance on standardized memory tests. Neuropsychology, 22(1), 10–16. https://doi.org/https://doi.org/10.1037/0894-4105.22.1.10
- Troyer, A. K., Rowe, G., Murphy, K. J., Levine, B., Leach, L., & Hasher, L. (2014). Development and evaluation of a self-administered on-line test of memory and attention for middle-aged and older adults. Frontiers in Aging Neuroscience, 6, 335. https://doi.org/https://doi.org/10.3389/fnagi.2014.00335
- Troyer, A. K., Vandermorris, S., & Murphy, K. J. (2016). Intraindividual variability in performance on associative memory tasks is elevated in amnestic mild cognitive impairment. Neuropsychologia, 90, 110–116. https://doi.org/https://doi.org/10.1016/j.neuropsychologia.2016.06.011
- Twamley, E. W., Ropacki, S. A. L., & Bondi, M. W. (2006). Neuropsychological and neuroimaging changes in preclinical Alzheimer’s disease. Journal of the International Neuropsychological Society, 12(5), 707–735. https://doi.org/https://doi.org/10.1017/S1355617706060863
- Vaughan, L., Leng, I., Dagenbach, D., Resnick, S. M., Rapp, S. R., Jennings, J. M., Brunner, R. L., Simpson, S. L., Beavers, D. P., Coker, L. H., Gaussoin, S. A., Sink, K. M., & Espeland, M. A. (2013). Intraindividual variability in domain-specific cognition and risk of mild cognitive impairment and dementia. Current Gerontology and Geriatrics Research, 2013, 1–10. https://doi.org/https://doi.org/10.1155/2013/495793
- Villemagne, V. L., Burnham, S., Bourgeat, P., Brown, B., Ellis, K. A., Salvado, O., Szoeke, C., Macaulay, S. L., Martins, R., Maruff, P., Ames, D., Rowe, C. C., & Masters, C. L. (2013). Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: A prospective cohort study. The Lancet Neurology, 12(4), 357–367. https://doi.org/https://doi.org/10.1016/S1474-4422(13)70044-9
- Watermeyer, T., Goerdten, J., Johansson, B., & Muniz-Terrera, G. (2020). Cognitive dispersion and ApoEe4 genotype predict dementia diagnosis in 8-year follow-up of the oldest-old. Age and Ageing, 50(3), 868–874.
- Wechsler, D. (1987). Manual for the Wechsler memory scale - Revised. The Psychological Corporation.
- Wechsler, D. (1997). Wechsler adult intelligence scale (3rd ed.). The Psychological Corporation.
- Wechsler, D. (1999). Wechsler abbreviated scale of intelligence. The Psychological Corporation.
- Welch, B. L. (1947). The generalization of student’s problem when several different population variances are involved. Biometrika, 34(1/2), 28–35. https://doi.org/https://doi.org/10.2307/2332510
- West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Sage Publications, Inc.
- Westerberg, C. E., Paller, K. A., Weintraub, S., Mesulam, -M.-M., Holdstock, J. S., Mayes, A. R., & Reber, P. J. (2006). When memory does not fail: Familiarity-based recognition in mild cognitive impairment and Alzheimer’s disease. Neuropsychology, 20(2), 193–205. https://doi.org/https://doi.org/10.1037/0894-4105.20.2.193
- Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.-O., Nordberg, A., Backman, L., Albert, M., Almkvist, O., Arai, H., Basun, H., Blennow, K., De Leon, M., DeCarli, C., Erkinjuntti, T., Giacobini, E., Graff, C., Hardy, J., Jorm, A., … Petersen, R. C. (2004). Mild cognitive impairment - beyond controversies, towards a consensus: Report of the international working group on mild cognitive impairment. Journal of Internal Medicine, 256(3), 240–246. https://doi.org/https://doi.org/10.1111/j.1365-2796.2004.01380.x
- Ylikoski, R., Ylikoski, A., Keskivaara, P., Tilvis, R., Sulkava, R., & Erkinjuntti, T. (1999). Heterogeneity of cognitive profiles in aging: Successful aging, normal aging, and individuals at risk for cognitive decline. European Journal of Neurology, 6(6), 645–652. https://doi.org/https://doi.org/10.1046/j.1468-1331.1999.660645.x
- Zhang, Y., Han, B., Verhaeghen, P., & Nilsson, L.-G. (2007). Executive functioning in older adults with mild cognitive impairment: MCI has effects on planning, but not on inhibition. Aging, Neuropsychology, and Cognition, 14(6), 557–570. https://doi.org/https://doi.org/10.1080/13825580600788118