Flynn wrote a book devoted to the Flynn effect, featuring his theoretical explanation of why the intelligence of worldwide populations has apparently increased from generation to generation. The essence of his theorizing is that because of the societal impact of scientific technology, people of today are much more guided by abstract, rather than concrete, approaches to problem solving. He bases his theory in large part on gains on specific tasks, most notably Raven’s matrices, Wechsler Intelligence Scale for Children (WISC) Performance subtests, and, most important, on WISC Similarities. The gains on these separate tasks over more than half a century (1947-2002) are striking. However, Flynn failed to take into account the sweeping changes in test content, administration procedures, and scoring guidelines when the 1974 WISC-R was developed from the 1949 WISC. These substantial changes challenge the meaningfulness of comparing children’s performance in 1947 with their performance in 2002 on Similarities and other WISC subtests— and therefore challenge Flynn’s explanation of the effect that bears his name.

The two featured articles and eight commentaries on the WISC-IV (Wechsler, 2003) and WAIS-IV (Wechsler, 2008) in this special issue of Journal of Psychoeducational Assessment are of exceptional quality. As a collective, this special issue greatly advances the field of cognitive assessment by intelligently synthesizing the best of methodology (confirmatory factor analysis) with the best of theory (Cattell–Horn–Carroll). The Weiss et al. articles represent sophisticated approaches to test validation and interpretation and the commentaries deal with applications, extensions, and limitations of the findings. This “response to the respondents” focuses on Wechsler’s approach to assessment, historical antecedents of factor analysis (especially the contributions of Jacob Cohen in the 1950s), and the “intelligent testing” model of test interpretation.

The literature on children born prematurely has consistently shown that full-term babies outperform preterm babies by about 12 IQ points, even when tested as adolescents, and this advantage for full-term infants extends to the language and motor domains as well. The results of comprehensive meta-analyses suggest that the degree of prematurity greatly influences later test performance, but these inferences are based on data from an array of separate studies with no control of potential confounding variables such as age. This study analyzed Bayley-4 data for 66 extremely premature infants and toddlers (<32 weeks), 70 moderately premature children (32–36 weeks), and 133 full-term children. All groups were carefully matched on key background variables by the test publisher during the standardization of the Bayley-4. This investigation analyzed data on the five subtests: cognitive, expressive communication, receptive communication, fine motor, and gross motor. A multivariate analysis of covariance (MANCOVA) assessed for group mean differences across the three subsamples, while controlling for the children’s age. Extremely premature children scored significantly lower than moderately premature children on all subtests, and both preterm groups were significantly outscored by the full-term sample across all domains. In each set of comparisons, the cognitive and motor subtests yielded the largest differences, whereas language development, both expressive and receptive, appeared the least impacted by prematurity. A follow-up MANOVA was conducted to examine full-term versus preterm discrepancies on the five subtests for infants (2–17 months) vs. toddlers (18–42 months). For that analysis, the two preterm groups were combined into a single preterm sample, and a significant interaction between the age level and group (full-term vs. preterm) was found. Premature infants scored lower than premature toddlers on receptive communication, fine motor, and cognitive. Neither expressive communication nor gross motor produced significant discrepancies between age groups The findings of this study enrich the preterm literature on the degree of prematurity; the age-based interactions have implications for which abilities are most likely to improve as infants grow into toddlerhood.

U. S. Supreme Court justices and other federal judges are, effectively, appointed for life, with no built-in check on their cognitive functioning as they approach old age. There is about a century of research on aging and intelligence that shows the vulnerability of processing speed, fluid reasoning, visual-spatial processing, and working memory to normal aging for men and women at all levels of education; even the maintained ability of crystallized knowledge declines in old age. The vulnerable abilities impact a person’s decision-making and problem solving; crystallized knowledge, by contrast, measures a person’s general knowledge. The aging-IQ data provide a rationale for assessing the key cognitive abilities of anyone who is appointed to the federal judiciary. Theories of multiple cognitive abilities and processes, most notably the Cattell-Horn-Carroll (CHC) model, provide a well-researched blueprint for interpreting the plethora of findings from studies of IQ and aging. Sophisticated technical advances in test construction, especially in item-response theory and computerized-adaptive testing, allow for the development of reliable and valid theory-based tests of cognitive functioning. Such assessments promise to be a potentially useful tool for evaluating federal judges to assess the impact of aging on their ability to perform at a level their positions deserve, perhaps to measure their competency to serve the public intelligently. It is proposed that public funding be made available to appoint a panel of experts to develop and validate an array of computerized cognitive tests to identify those justices who are at risk of cognitive impairment.