References
- Arias, V. B., Ponce, F. P., & Núñez, D. E. (2018). Bifactor models of attention-deficit/hyperactivity disorder (ADHD): An evaluation of three necessary but underused psychometric indexes. Assessment, 25(7), 885–897. https://doi.org/10.1177/1073191116679260
- Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology, 49(1), 5–28. https://doi.org/10.1080/713755608
- Balota, D. A., & Spieler, D. H. (1999). Word frequency, repetition, and lexicality effects in word recognition tasks: Beyond measures of central tendency. Journal of Experimental Psychology: General, 128(1), 32–55. https://doi.org/10.1037/0096-3445.128.1.32
- Beck, J. M., Ma, W. J., Kiani, R., Hanks, T., Churchland, A. K., Roitman, J., … Pouget, A. (2008). Probabilistic population codes for Bayesian decision making. Neuron, 60(6), 1142–1152. https://doi.org/10.1016/j.neuron.2008.09.021
- Bornovalova, M. A., Choate, A. M., Fatimah, H., Petersen, K. J., & Wiernik, B. M. (2020). Appropriate use of bifactor analysis in psychopathology research: Appreciating benefits and limitations. Biological Psychiatry, 88(1), 18–27. https://doi.org/10.1016/j.biopsych.2020.01.013
- Boywitt, C. D., & Rummel, J. (2012). A diffusion model analysis of task interference effects in prospective memory. Memory & Cognition, 40(1), 70–82. https://doi.org/10.3758/s13421-011-0128-6
- Brown, T. A. (2015). Confirmatory factor analysis for applied research. Guilford Publications.
- Brunner, M., Nagy, G., & Wilhelm, O. (2012). A tutorial on hierarchically structured constructs. Journal of Personality, 80(4), 796–846. https://doi.org/10.1111/j.1467-6494.2011.00749.x
- Buzy, W. M., Medoff, D. R., & Schweitzer, J. B. (2009). Intra-individual variability among children with ADHD on a working memory task: An ex-Gaussian approach. Child Neuropsychology, 15(5), 441–459. https://doi.org/10.1080/09297040802646991
- Caci, H. M., Morin, A. J., & Tran, A. (2016). Teacher ratings of the ADHD-RS IV in a community sample: Results from the ChiP-ARD study. Journal of Attention Disorders, 20(5), 434–444. https://doi.org/10.1177/1087054712473834
- Canivez, G. L. (2016). Bifactor modeling in construct validation of multifactored tests: Implications for understanding multidimensional constructs and test interpretation. In K. Schweizer & C. DiStefano (Eds.), Principles and methods of test construction: Standards and recent advancements (pp. 247–271). Hogrefe.
- Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., … Poulton, R. (2014). The p factor: One general psychopathology factor in the structure of psychiatric disorders? Clinical Psychological Science, 2(2), 119–137. https://doi.org/10.1177/2167702613497473
- Castellanos, F. X., & Tannock, R. (2002). Neuroscience of attention-deficit/hyperactivity disorder: The search for endophenotypes. Nature Reviews Neuroscience, 3(8), 617–628. https://doi.org/10.1038/nrn896
- Conners, C. K. (2001). Conners’ rating scales-revised technical manual. Multi-Health Systems.
- Cyders, M. A., & Coskunpinar, A. (2011). Measurement of constructs using self-report and behavioral lab tasks: Is there overlap in nomothetic span and construct representation for impulsivity? Clinical Psychology Review, 31(6), 965–982. https://doi.org/10.1016/j.cpr.2011.06.001
- Cyders, M. A., & Smith, G. T. (2007). Mood-based rash action and its components: Positive and negative urgency. Personality and Individual Differences, 43(4), 839–850. https://doi.org/10.1016/j.paid.2007.02.008
- DuPaul, G. J., Power, T. J., Anastopoulos, A. D., & Reid, R. (1998). ADHD rating scale—IV: Checklists, norms, and clinical interpretation. Guilford Press.
- DuPaul, G. J., Reid, R., Anastopoulos, A. D., Lambert, M. C., Watkins, M. W., & Power, T. J. (2016). Parent and teacher ratings of attention-deficit/hyperactivity disorder symptoms: Factor structure and normative data. Psychological Assessment, 28(2), 214–225. https://doi.org/10.1037/pas0000166
- Dutilh, G., Forstmann, B. U., Vandekerckhove, J., & Wagenmakers, E. J. (2013). A diffusion model account of age differences in posterror slowing. Psychology and Aging, 28(1), 64–76. https://doi.org/10.1037/a0029875
- Dutilh, G., Krypotos, A. M., & Wagenmakers, E. J. (2011). Task-related versus stimulus-specific practice. Experimental Psychology, 58(6), 434–442. https://doi.org/10.1027/1618-3169/a000111
- Epstein, J. N., Conners, C. K., Hervey, A. S., Tonev, S. T., Eugene Arnold, L., & Abikoff, H. B., & M. T. A. Cooperative Study Group. (2006). Assessing medication effects in the MTA study using neuropsychological outcomes. Journal of Child Psychology and Psychiatry, 47(5), 446–456. https://doi.org/10.1111/j.1469-7610.2005.01469.x
- Epstein, J. N., Langberg, J. M., Rosen, P. J., Graham, A., Narad, M. E., Antonini, T. N., … Altaye, M. (2011). Evidence for higher reaction time variability for children with ADHD on a range of cognitive tasks including reward and event rate manipulations. Neuropsychology, 25(4), 427–441. https://doi.org/10.1037/a0022155
- Epstein, J. N., & Loren, R. E. A. (2013). Changes in the definition of ADHD in DSM-5: Subtle but important. Neuropsychiatry, 3(5), 455–458. https://doi.org/10.2217/npy.13.59
- Feldman, J. S., & Huang-Pollock, C. L. (2020). A new spin on spatial cognition in ADHD: A diffusion model decomposition of mental rotation. Journal of the International Neuropsychological Society. Advance online publication. https://doi.org/10.1017/S1355617720001198
- Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. https://doi.org/10.1037/1082-989X.9.4.466
- Frazier, T. W., Demaree, H. A., & Youngstrom, E. A. (2004). Meta-analysis of intellectual and neuropsychological test performance in attention-deficit/hyperactivity disorder. Neuropsychology, 18(3), 543–555. https://doi.org/10.1037/0894-4105.18.3.543
- Friedman, N. P., Du Pont, A., Corley, R. P., & Hewitt, J. K. (2018). Longitudinal relations between depressive symptoms and executive functions from adolescence to early adulthood: A twin study. Clinical Psychological Science, 6(4), 543–560. https://doi.org/10.1177/2167702618766360
- Friedman, N. P., Hatoum, A. S., Gustavson, D. E., Corley, R. P., Hewitt, J. K., & Young, S. E. (2020). Executive functions and impulsivity are genetically distinct and independently predict psychopathology: Results from two adult twin studies. Clinical Psychological Science, 8(3), 519–538. https://doi.org/10.1177/2167702619898814
- Gerst, E. H., Cirino, P. T., Fletcher, J. M., & Yoshida, H. (2017). Cognitive and behavioral rating measures of executive function as predictors of academic outcomes in children. Child Neuropsychology, 23(4), 381–407. https://doi.org/10.1080/09297049.2015.1120860
- Gignac, G. E., & Watkins, M. W. (2013). Bifactor modeling and the estimation of model-based reliability in the WAIS-IV. Multivariate Behavioral Research, 48(5), 639–662. https://doi.org/10.1080/00273171.2013.804398
- Goh, P. K., Lee, C. A., Bansal, P. S., Aguerrevere, L. E., Rucker, A. T., & Martel, M. M. (2020). Interpretability and validity of a bifactor model of ADHD in young adults: Assessing the general “g” and specific IA and HI factors. Journal of Psychopathology and Behavioral Assessment, 42(2), 222–236. https://doi.org/10.1007/s10862-019-09774-7
- Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. Annual Review of Neuroscience, 30(1), 535–574. https://doi.org/10.1146/annurev.neuro.29.051605.113038
- Gomez, R., Vance, A., & Gomez, R. M. (2018). Validity of the ADHD bifactor model in general community samples of adolescents and adults, and a clinic-referred sample of children and adolescents. Journal of Attention Disorders, 22(14), 1307–1319. https://doi.org/10.1177/1087054713480034
- Hancock, G. R., & Mueller, R. O. (2001). Rethinking construct reliability within latent variable systems. In R. Cudeck, S. Du Toit, & D. Sorbom (Eds.), Structural equation modeling: Present and future—A Festschrift in honor of Karl Joreskog (pp. 195–216). Scientific Software.
- Hatoum, A. S., Rhee, S. H., Corley, R. P., Hewitt, J. K., & Friedman, N. P. (2018). Do executive functions explain the covariance between internalizing and externalizing behaviors? Development and Psychopathology, 30(4), 1371–1387. https://doi.org/10.1017/S0954579417001602
- Herlihey, T. A., Black, S. E., & Ferber, S. (2013). Action modulated cognition: The influence of sensori–motor experience on the global processing bias. Neuropsychologia, 51(10), 1973–1979. https://doi.org/10.1016/j.neuropsychologia.2013.06.014
- Hervey, A. S., Epstein, J. N., Curry, J. F., Tonev, S., Eugene Arnold, L., Conners, C. K., … Hechtman, L. (2006). Reaction time distribution analysis of neuropsychological performance in an ADHD sample. Child Neuropsychology, 12(2), 125–140. https://doi.org/10.1080/09297040500499081
- Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modeling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53–60. https://www.researchgate.net/publication/254742561
- Huang-Pollock, C. L., Ratcliff, R., McKoon, G., Roule, A., Warner, T., Feldman, J. S., & Wise, S. (2020). A diffusion model analysis of sustained attention in children with attention deficit hyperactivity disorder. Neuropsychology, 34(6), 641–653. https://doi.org/10.1037/neu0000636
- Huang-Pollock, C. L., Ratcliff, R., McKoon, G., Shapiro, Z., Weigard, A., & Galloway-Long, H. (2017). Using the diffusion model to explain cognitive deficits in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 45(1), 57–68. https://doi.org/10.1007/s10802-016-0151-y
- Huang-Pollock, C. L., Shapiro, Z., Galloway-Long, H., & Weigard, A. (2017). Is poor working memory a transdiagnostic risk factor for psychopathology? Journal of Abnormal Child Psychology, 45(8), 1477–1490. https://doi.org/10.1007/s10802-016-0219-8
- Irwin, L. N., Kofler, M. J., Soto, E. F., & Groves, N. B. (2019). Do children with attention-deficit/hyperactivity disorder (ADHD) have set shifting deficits? Neuropsychology, 33(4), 470–481. https://doi.org/10.1037/neu0000546
- Jonsdottir, S., Bouma, A., Sergeant, J. A., & Scherder, E. J. A. (2006). Relationships between neuropsychological measures of executive function and behavioral measures of ADHD symptoms and comorbid behavior. Archives of Clinical Neuropsychology, 21(5), 383–394. https://doi.org/10.1016/j.acn.2006.05.003
- Karalunas, S. L., Geurts, H. M., Konrad, K., Bender, S., & Nigg, J. T. (2014). Annual research review: Reaction time variability in ADHD and autism spectrum disorders: Measurement and mechanisms of a proposed trans‐diagnostic phenotype. Journal of Child Psychology and Psychiatry, 55(6), 685–710. https://doi.org/10.1111/jcpp.12217
- Karalunas, S. L., & Huang-Pollock, C. L. (2013). Integrating impairments in reaction time and executive function using a diffusion model framework. Journal of Abnormal Child Psychology, 41(5), 837–850. https://doi.org/10.1007/s10802-013-9715-2
- Karalunas, S. L., Huang-Pollock, C. L., & Nigg, J. T. (2012). Decomposing attention-deficit/hyperactivity disorder (ADHD)-related effects in response speed and variability. Neuropsychology, 26(6), 684–694. https://doi.org/10.1037/a0029936
- Karr, J. E., Areshenkoff, C. N., Rast, P., Hofer, S. M., Iverson, G. L., & Garcia-Barrera, M. A. (2018). The unity and diversity of executive functions: A systematic review and re-analysis of latent variable studies. Psychological Bulletin, 144(11), 1147–1185. https://doi.org/10.1037/bul0000160
- Lahey, B. B., Applegate, B., Hakes, J. K., Zald, D. H., Hariri, A. R., & Rathouz, P. J. (2012). Is there a general factor of prevalent psychopathology during adulthood? Journal of Abnormal Psychology, 121(4), 971–977. https://doi.org/10.1037/a0028355
- Lahey, B. B., Krueger, R. F., Rathouz, P. J., Waldman, I. D., & Zald, D. H. (2017). A hierarchical causal taxonomy of psychopathology across the life span. Psychological Bulletin, 143(2), 142–186. https://doi.org/10.1037/bul0000069
- Larsen, A. (2014). Deconstructing mental rotation. Journal of Experimental Psychology: Human Perception and Performance, 40(3), 1072–1091. https://doi.org/10.1037/a0035648
- Lee, S. S., Lahey, B. B., Owens, E. B., & Hinshaw, S. P. (2008). Few preschool boys and girls with adhd are well-adjusted during adolescence. Journal of Abnormal Child Psychology, 36(3), 373–383. https://doi.org/10.1007/s10802-007-9184-6
- Lerche, V., & Voss, A. (2020). When accuracy rates and mean response times lead to false conclusions: A simulation study based on the diffusion model. The Quantitative Methods for Psychology, 16(2), 107–119. https://doi.org/10.20982/tqmp.16.2.p107
- Leth-Steensen, C., Elbaz, Z. K., & Douglas, V. I. (2000). Mean response times, variability, and skew in the responding of ADHD children: A response time distributional approach. Acta Psychologica, 104(2), 167–190. https://doi.org/10.1016/S0001-6918(00)00019-6
- Lezak, M. D. (1995). Executive functions and motor performance. In M. D. Lezak (Ed.), Neuropsychological assessment (pp. 650–685). Oxford University Press.
- Logan, G. D., Schachar, R. J., & Tannock, R. (1997). Impulsivity and inhibitory control. Psychological Science, 8(1), 60–64. https://doi.org/10.1111/j.1467-9280.1997.tb00545.x
- Madden, D. J., Gottlob, L. R., Denny, L. L., Turkington, T. G., Provenzale, J. M., Hawk, T. C., & Coleman, R. E. (1999). Aging and recognition memory: Changes in regional cerebral blood flow associated with components of reaction time distributions. Journal of Cognitive Neuroscience, 11(5), 511–520. https://doi.org/10.1162/089892999563571
- Martel, M. M., Schimmack, U., Nikolas, M., & Nigg, J. T. (2015). Integration of symptom ratings from multiple informants in ADHD diagnosis: A psychometric model with clinical utility. Psychological Assessment, 27(3), 1060. https://doi.org/10.1037/pas0000088
- Martel, M. M., Von Eye, A., & Nigg, J. T. (2010). Revisiting the latent structure of ADHD: Is there a ‘g’factor? Journal of Child Psychology and Psychiatry, 51(8), 905–914. https://doi.org/10.1111/j.1469-7610.2010.02232.x
- Martinussen, R., Hayden, J., Hogg-Johnson, S., & Tannock, R. (2005). A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 44(4), 377–384. https://doi.org/10.1097/01.chi.0000153228.72591.73
- Matzke, D., & Wagenmakers, E.-J. (2009). Psychological interpretation of the ex-gaussian and shifted wald parameters: A diffusion model analysis. Psychonomic Bulletin & Review, 16(5), 798–817. https://doi.org/10.3758/PBR.16.5.798
- McDonald, R. P. (1999). Test theory: A unified approach. Lawrence Erlbaum.
- Metin, B., Roeyers, H., Wiersema, J. R., Van Der Meere, J. J., Thompson, M., & Sonuga-Barke, E. (2013). ADHD performance reflects inefficient but not impulsive information processing: A diffusion model analysis. Neuropsychology, 27(2), 193–200. https://doi.org/10.1037/a0031533
- Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 21(1), 8–14. https://doi.org/10.1177/0963721411429458
- Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49–100. https://doi.org/10.1006/cogp.1999.0734
- Monsell, S., & Driver, J. (2000). Banishing the control homunculus. In S. Monsell & J. Driver (Eds.), Control of cognitive processes: Attention and performance XVIII (pp. 3–32). MIT Press.
- Moustafa, A. A., Kéri, S., Somlai, Z., Balsdon, T., Frydecka, D., Misiak, B., & White, C. (2015). Drift diffusion model of reward and punishment learning in schizophrenia: Modeling and experimental data. Behavioural Brain Research, 291, 147–154. https://doi.org/10.1016/j.bbr.2015.05.024
- Mulder, M. J., Bos, D., Weusten, J. M., Van Belle, J., Van Dijk, S. C., Simen, P., … Durston, S. (2010). Basic impairments in regulating the speed-accuracy tradeoff predict symptoms of attention-deficit/hyperactivity disorder. Biological Psychiatry, 68(12), 1114–1119. https://doi.org/10.1016/j.biopsych.2010.07.031
- Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive Psychology, 9(3), 353–383. https://doi.org/10.1016/0010-0285(77)90012-3
- Nigg, J. T., Willcutt, E. G., Doyle, A. E., & Sonuga-Barke, E. J. (2005). Causal heterogeneity in attention-deficit/hyperactivity disorder: Do we need neuropsychologically impaired subtypes? Biological Psychiatry, 57(11), 1224–1230. https://doi.org/10.1016/j.biopsych.2004.08.025
- Nunez, M. D., Vandekerckhove, J., & Srinivasan, R. (2017). How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters. Journal of Mathematical Psychology, 76(Part B), 117–130. https://doi.org/10.1016/j.jmp.2016.03.003
- Owens, E. B., Hinshaw, S. P., Lee, S. S., & Lahey, B. B. (2009). Few girls with childhood attention-deficit/hyperactivity disorder show positive adjustment during adolescence. Journal of Clinical Child & Adolescent Psychology, 38(1), 132–143. https://doi.org/10.1080/15374410802575313
- Philiastides, M. G., Ratcliff, R., & Sajda, P. (2006). Neural representation of task difficulty and decision making during perceptual categorization: A timing diagram. Journal of Neuroscience, 26(35), 8965–8975. https://doi.org/10.1523/JNEUROSCI.1655-06.2006
- Provost, A., & Heathcote, A. (2015). Titrating decision processes in the mental rotation task. Psychological Review, 122(4), 735–754. https://doi.org/10.1037/a0039706
- Provost, A., Johnson, B., Karayanidis, F., Brown, S. D., & Heathcote, A. (2013). Two routes to expertise in mental rotation. Cognitive Science, 37(7), 1321–1342. https://doi.org/10.1111/cogs.12042
- Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85(2), 59–108. https://doi.org/10.1037/0033-295X.85.2.59
- Ratcliff, R., Love, J., Thompson, C. A., & Opfer, J. E. (2012). Children are not like older adults: A diffusion model analysis of developmental changes in speeded responses. Child Development, 83(1), 367–381. https://doi.org/10.1111/j.1467-8624.2011.01683.x
- Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: Theory and data for two-choice decision tasks. Neural Computation, 20(4), 873–922. https://doi.org/10.1162/neco.2008.12-06-420
- Ratcliff, R., Philiastides, M., & Sajda, P. (2009). Quality of evidence for perceptual decision making is indexed by trial-to-trial variability of the EEG. Proceedings of the National Academy of Sciences, 106(16), 6539–6544. https://doi.org/10.1073/pnas.0812589106
- Ratcliff, R., Sederberg, P., Smith, T., & Childers, R. (2016). A single trial analysis of EEG in recognition memory: Tracking the neural correlates of memory strength. Neuropsychologia, 93(Part A), 128–141. https://doi.org/10.1016/j.neuropsychologia.2016.09.026
- Ratcliff, R., Thapar, A., & McKoon, G. (2001). The effects of aging on reaction time in a signal detection task. Psychology and Aging, 16(2), 323–341. https://doi.org/10.1037/0882-7974.16.2.323
- Ratcliff, R., & Tuerlinckx, F. (2002). Estimating parameters of the diffusion model: Approaches to dealing with contaminant reaction times and parameter variability. Psychonomic Bulletin & Review, 9(3), 438–481. https://doi.org/10.3758/BF03196302
- Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667–696. https://doi.org/10.1080/00273171.2012.715555
- Reise, S. P., Moore, T. M., & Haviland, M. G. (2010). Bifactor models and rotations: Exploring the extent to which multidimensional data yield univocal scale scores. Journal of Personality Assessment, 92(6), 544–559. https://doi.org/10.1080/00223891.2010.496477
- Reise, S. P., Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educational and Psychological Measurement, 73(1), 5–26. https://doi.org/10.1177/0013164412449831
- Reynolds, C. R., & Kamphaus, R. W. (2004). Behavior assessment system for children, (BASC-2). American Guidance Service.
- Rodenacker, K., Hautmann, C., Görtz-Dorten, A., & Döpfner, M. (2017). The factor structure of ADHD – Different models, analyses and informants in a bifactor framework. Journal of Psychopathology and Behavioral Assessment, 39(1), 92–102. https://doi.org/10.1007/s10862-016-9565-7
- Rommelse, N. N., Altink, M. E., Fliers, E. A., Martin, N. C., Buschgens, C. J., Hartman, C. A., … Oosterlaan, J. (2009). Comorbid problems in ADHD: Degree of association, shared endophenotypes, and formation of distinct subtypes. Implications for a future DSM. Journal of Abnormal Child Psychology, 37(6), 793–804. https://doi.org/10.1007/s10802-009-9312-6
- Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
- Rotello, C. M., & Zeng, M. (2008). Analysis of RT distributions in the remember—know paradigm. Psychonomic Bulletin & Review, 15(4), 825–832. https://doi.org/10.3758/PBR.15.4.825
- Salum, G., Sergeant, J., Sonuga-Barke, E., Vandekerckhove, J., Gadelha, A., Pan, P., … Rohde, L. A. P. (2014). Specificity of basic information processing and inhibitory control in attention deficit hyperactivity disorder. Psychological Medicine, 44(3), 617–631. https://doi.org/10.1017/S0033291713000639
- Salum, G., Sonuga-Barke, E., Sergeant, J., Vandekerckhove, J., Gadelha, A., Moriyama, T., … Rohde, L. A. P. (2014). Mechanisms underpinning inattention and hyperactivity: Neurocognitive support for ADHD dimensionality. Psychological Medicine, 44(15), 3189–3201. https://doi.org/10.1017/S0033291714000919
- Schachar, R. J., Chen, S., Logan, G. D., Ornstein, T. J., Crosbie, J., Ickowicz, A., & Pakulak, A. (2004). Evidence for an error monitoring deficit in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 32(3), 285–293. https://doi.org/10.1023/B:JACP.0000026142.11217.f2
- Schmiedek, F., Oberauer, K., Wilhelm, O., Süß, H.-M., & Wittmann, W. W. (2007). Individual differences in components of reaction time distributions and their relations to working memory and intelligence. Journal of Experimental Psychology: General, 136(3), 414–429. https://doi.org/10.1037/0096-3445.136.3.414
- Schmitz, F., & Voss, A. (2012). Decomposing task-switching costs with the diffusion model. Journal of Experimental Psychology: Human Perception and Performance, 38(1), 222–250. https://doi.org/10.1037/a0026003
- Schuch, S. (2016). Task inhibition and response inhibition in older vs. younger adults: A diffusion model analysis. Frontiers in Psychology, 7, 1722. https://doi.org/10.3389/fpsyg.2016.01722
- Shaffer, D., Fisher, P., & Lucas, C. (1997). NIMH diagnostic interview schedule for children—IV. New York: Ruane Center for Early Diagnosis, Division of Child Psychiatry, Columbia University.
- Shapiro, Z., & Huang-Pollock, C. L. (2019). A diffusion-model analysis of timing deficits among children with ADHD. Neuropsychology, 33(6), 883–892. https://doi.org/10.1037/neu0000562
- Sharma, L., Markon, K. E., & Clark, L. A. (2014). Toward a theory of distinct types of “impulsive” behaviors: A meta-analysis of self-report and behavioral measures. Psychological Bulletin, 140(2), 374–408. https://doi.org/10.1037/a0034418
- Sonuga-Barke, E. J. S. (2005). Causal models of attention-deficit/hyperactivity disorder: From common simple deficits to multiple developmental pathways. Biological Psychiatry, 57(11), 1231–1238. https://doi.org/10.1016/j.biopsych.2004.09.008
- Sonuga-Barke, E. P. D., Bitsakou, P. P. D., & Thompson, M. M. D. (2010). Beyond the dual pathway model: Evidence for the dissociation of timing, inhibitory, and delay-related impairments in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 49(4), 345–355. https://doi.org/10.1016/j.jaac.2009.12.018
- Spieler, D. H., Balota, D. A., & Faust, M. E. (1996). Stroop performance in healthy younger and older adults and in individuals with dementia of the Alzheimer’s type. Journal of Experimental Psychology: Human Perception and Performance, 22(2), 461–479. https://doi.org/10.1037//0096-1523.22.2.461
- Stucky, B. D., & Edelen, M. O. (2014). Using hierarchical IRT models to create unidimensional measures from multidimensional data. In S. P. Reise & D. A. Revicki (Eds.), Handbook of item response theory modeling: Applications to typical performance assessment (pp. 183–206). Routledge/Taylor & Francis Group.
- Turner, B. M., Van Maanen, L., & Forstmann, B. U. (2015). Informing cognitive abstractions through neuroimaging: The neural drift diffusion model. Psychological Review, 122(2), 312–336. https://doi.org/10.1037/a0038894
- Van Der Ven, S. H. G., Kroesbergen, E. H., Boom, J., & Leseman, P. P. M. (2013). The structure of executive functions in children: A closer examination of inhibition, shifting, and updating. British Journal of Developmental Psychology, 31(1), 70–87. https://doi.org/10.1111/j.2044-835X.2012.02079.x
- Verbruggen, F., & Logan, G. D. (2008). After-effects of goal shifting and response inhibition: A comparison of the stop-change and dual-task paradigms. The Quarterly Journal of Experimental Psychology, 61(8), 1151–1159. https://doi.org/10.1080/17470210801994971
- Verbruggen, F., McLaren, I. P. L., & Chambers, C. D. (2014). Banishing the control homunculi in studies of action control and behavior change. Perspectives on Psychological Science, 9(5), 497–524. https://doi.org/10.1177/1745691614526414
- Verbruggen, F., Stevens, T., & Chambers, C. D. (2014). Proactive and reactive stopping when distracted: An attentional account. Journal of Experimental Psychology: Human Perception and Performance, 40(4), 1295–1300. https://doi.org/10.1037/a0036542
- Vogan, V. M., Morgan, B. R., Lee, W., Powell, T. L., Smith, M. L., & Taylor, M. J. (2014). The neural correlates of visuo-spatial working memory in children with autism spectrum disorder: Effects of cognitive load. Journal of Neurodevelopmental Disorders, 6(1), 19. https://doi.org/10.1186/1866-1955-6-19
- Voss, A., Rothermund, K., & Voss, J. (2004). Interpreting the parameters of the diffusion model: An empirical validation. Memory & Cognition, 32(7), 1206–1220. https://doi.org/10.3758/BF03196893
- Voss, A., & Voss, J. (2007). Fast-dm: A free program for efficient diffusion model analysis. Behavior Research Methods, 39(4), 767–775. https://doi.org/10.3758/BF03192967
- Wagenmakers, E.-J. (2009). Methodological and empirical developments for the Ratcliff diffusion model of response times and accuracy. European Journal of Cognitive Psychology, 21(5), 641–671. https://doi.org/10.1080/09541440802205067
- Wechsler, D. (2003). Weschler intelligence scale for children—IV, technical manual. The Psychological Corporation.
- Weigard, A., Heathcote, A., Matzke, D., & Huang-Pollock, C. L. (2019). Cognitive modeling suggests that attentional failures drive longer stop-signal reaction time estimates in attention deficit/hyperactivity disorder. Clinical Psychological Science, 7(4), 856–872. https://doi.org/10.1177/2167702619838466
- Weigard, A., & Huang-Pollock, C. L. (2014). A diffusion modeling approach to understanding contextual cueing effects in children with ADHD. Journal of Child Psychology and Psychiatry, 55(12), 1336–1344. https://doi.org/10.1111/jcpp.12250
- Weigard, A., & Huang-Pollock, C. L. (2017). The role of speed in ADHD-related working memory deficits: A time-based resource-sharing and diffusion model account. Clinical Psychological Science, 5(2), 195–211. https://doi.org/10.1177/2167702616668320
- White, C. N., Congdon, E., Mumford, J. A., Karlsgodt, K. H., Sabb, F. W., Freimer, N. B., … Poldrack, R. A. (2014). Decomposing decision components in the stop-signal task: A model-based approach to individual differences in inhibitory control. Journal of Cognitive Neuroscience, 26(8), 1601–1614. https://doi.org/10.1162/jocn_a_00567
- White, C. N., Ratcliff, R., Vasey, M., & McKoon, G. (2009). Dysphoria and memory for emotional material: A diffusion-model analysis. Cognition & Emotion, 23(1), 181–205. https://doi.org/10.1080/02699930801976770
- White, C. N., Skokin, K., Carlos, B., & Weaver, A. (2016). Using decision models to decompose anxiety-related bias in threat classification. Emotion, 16(2), 196–207. https://doi.org/10.1037/emo0000109
- Willcutt, E. G., Doyle, A. E., Nigg, J. T., Faraone, S. V., & Pennington, B. F. (2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: A meta-analytic review. Biological Psychiatry, 57(11), 1336–1346. https://doi.org/10.1016/j.biopsych.2005.02.006
- Willcutt, E. G., Nigg, J. T., Pennington, B. F., Solanto, M. V., Rohde, L. A., Tannock, R., … Lahey, B. B. (2012). Validity of DSM-IV attention deficit/hyperactivity disorder symptom dimensions and subtypes. Journal of Abnormal Psychology, 121(4), 991–1010. https://doi.org/10.1037/a0027347
- Willoughby, M. T., & Blanton, Z. E., & Family Life Project. (2015). Replication and external validation of a bi-factor parameterization of attention deficit/hyperactivity symptomatology. Journal of Clinical Child & Adolescent Psychology, 44(1), 68–79. https://doi.org/10.1080/15374416.2013.850702
- Wright, L., Lipszyc, J., Dupuis, A., Thayapararajah, S. W., & Schachar, R. (2014). Response inhibition and psychopathology: A meta-analysis of go/no-go task performance. Journal of Abnormal Psychology, 123(2), 429–439. https://doi.org/10.1037/a0036295