The List Sorting Working Memory Test was designed to assess working memory (WM) as part of the NIH Toolbox Cognition Battery. List Sorting is a sequencing task requiring children and adults to sort and sequence stimuli that are presented visually and auditorily. Validation data are presented for 268 participants ages 20 to 85 years. A subset of participants (N=89) was retested 7 to 21 days later. As expected, the List Sorting Test had moderately high correlations with other measures of working memory and executive functioning (convergent validity) but a low correlation with a test of receptive vocabulary (discriminant validity). Furthermore, List Sorting demonstrates expected changes over the age span and has excellent test–retest reliability. Collectively, these results provide initial support for the construct validity of the List Sorting Working Memory Measure as a measure of working memory. However, the relationship between the List Sorting Test and general executive function has yet to be determined. (JINS, 2014, 20, 1–12)

The NIH Toolbox (NIHTB) Pattern Comparison Processing Speed Test was developed to assess processing speed within the NIHTB for the Assessment of Neurological Behavior and Function Cognition Battery (NIHTB-CB). This study highlights validation data collected in adults ages 18–85 on this measure and reports descriptive data, test–retest reliability, construct validity, and preliminary work creating a composite index of processing speed. Results indicated good test–retest reliability. There was also evidence for both convergent and discriminant validity; the Pattern Comparison Processing Speed Test demonstrated moderate significant correlations with other processing speed tests (i.e., WAIS-IV Coding, Symbol Search and Processing Speed Index), small significant correlations with measures of working memory (i.e., WAIS-IV Letter-Number Sequencing and PASAT), and non-significant correlations with a test of vocabulary comprehension (i.e., PPVT-IV). Finally, analyses comparing and combining scores on the NIHTB Pattern Comparison Processing Speed Test with other measures of simple reaction time from the NIHTB-CB indicated that a Processing Speed Composite score performed better than any test examined in isolation. The NIHTB Pattern Comparison Processing Speed Test exhibits several strengths: it is appropriate for use across the lifespan (ages, 3–85 years), it is short and easy to administer, and it has high construct validity. (JINS, 2014, 20, 1–12)

This study introduces a special series on validity studies of the Cognition Battery (CB) from the U.S. National Institutes of Health Toolbox for the Assessment of Neurological and Behavioral Function (NIHTB) (Gershon, Wagster et al., 2013) in an adult sample. This first study in the series describes the sample, each of the seven instruments in the NIHTB-CB briefly, and the general approach to data analysis. Data are provided on test–retest reliability and practice effects, and raw scores (mean, standard deviation, range) are presented for each instrument and the gold standard instruments used to measure construct validity. Accompanying papers provide details on each instrument, including information about instrument development, psychometric properties, age and education effects on performance, and convergent and discriminant construct validity. One study in the series is devoted to a factor analysis of the NIHTB-CB in adults and another describes the psychometric properties of three composite scores derived from the individual measures representing fluid and crystallized abilities and their combination. The NIHTB-CB is designed to provide a brief, comprehensive, common set of measures to allow comparisons among disparate studies and to improve scientific communication. (JINS, 2014, 20, 1–12)

While some of the modifications made to produce the WAIS–III and WMS–III (Wechsler, 1997a, 1997b) make sense from a neuropsychological standpoint, there are many questions still unanswered about the validity and reliability of these tests and their ultimate utility to neuropsychologists. The new tests have been criticized for having long administration times, which is problematic given pressures to decrease rather than increase the length and cost of neuropsychological evaluations (Ryan et al., 1998). Clinical neuropsychologists want to know if these tests can help them evaluate their patients more accurately with greater sensitivity and specificity than the alternatives, and experimental neuropsychologists want to know if they can help answer theoretical questions.

The criterion validity of the new subtests from the Wechsler Adult Intelligence Scale–Third Edition (WAIS–III; Wechsler, 1997) was evaluated in a sample of 100 patients with traumatic brain injury (TBI). Letter–Number Sequencing and Symbol Search, but not Matrix Reasoning, yielded statistically significant differences in performance between patients with moderate–severe TBI, patients with mild TBI, and demographically matched controls. Level of education accounted for a statistically significant amount of variance in the performance of patients with TBI, in addition to that explained by injury severity variables. It is concluded that Letter–Number Sequencing and Symbol Search have satisfactory criterion validity, but that they need to be supplemented with other measures in the context of neuropsychological evaluations. Matrix Reasoning, on the other hand, is not sensitive to the sequelae of TBI and more studies are needed to determine how it can be used for neuropsychological assessment purposes. (JINS, 2001, 7, 892–898.)

Since memory performance expectations may be IQ-based, unidirectional base rate data for IQ-Memory Score discrepancies are provided in the WAIS–III/WMS–III Technical Manual. The utility of these data partially rests on the assumption that discrepancy base rates do not vary across ability levels. FSIQ stratified base rate data generated from the standardization sample, however, demonstrate substantial variability across the IQ spectrum. A superiority of memory score over FSIQ is typical at lower IQ levels, whereas the converse is true at higher IQ levels. These data indicate that the use of IQ–memory score unstratified “simple difference” tables could lead to erroneous conclusions for clients with low or high IQ. IQ stratified standardization base rate data are provided as a complement to the “predicted difference” method detailed in the Technical Manual. (JINS, 2001, 7, 875–880.)

Reliability estimates for psychological tests are almost always reported for nonclinical populations (e.g., the normative samples). Such practice will no longer be sufficient as the new standards for testing call for an adequate assessment of psychometric properties within the specific population being tested. The purpose of this study was to provide internal consistency reliability estimates for clinical groups on the Wechsler Adult Intelligence Scale–Third Edition. The study included data from 403 clinical participants composed of 10 groups of adults recruited as part of the WAIS–III clinical validity studies. Split-half reliability coefficients were obtained for these groups replicating the procedure used in the WAIS–III. With 8 of the clinical groups, the split-half reliability coefficients were comparable to, or even higher than, those reported for the WAIS–III standardization sample. In general, the split-half coefficients for the Verbal subtests tended to be higher than the coefficients for the Performance subtests. The high magnitude and general pattern of these coefficients demonstrate that the WAIS–III scales do not include additional error variance above and beyond what is reported in the WAIS–III–WMS–III Technical Manual when it was used to assess certain clinical groups. For the ADHD/ADD and learning disabilities groups, however, the internal consistencies coefficients of some subtests were relatively lower, although not statistically significant, than the normative sample. These findings may reflect more heterogeneity within the groups. The implications for assessment and for using alternate methods of determining the psychometric properties in these populations are discussed. (JINS, 2001, 7, 862–866.)