The stability of cognitive abilities: A meta-analytic review of longitudinal studies.

Cognitive abilities, including general intelligence and domain-specific abilities such as fluid reasoning, comprehension knowledge, working memory capacity, and processing speed, are regarded as some of the most stable psychological traits, yet there exist no large-scale systematic efforts to document the specific patterns by which their rank-order stability changes over age and time interval, or how their stability differs across abilities, tests, and populations. Determining the conditions under which cognitive abilities exhibit high or low degrees of stability is critical not just to theory development but to applied contexts in which cognitive assessments guide decisions regarding treatment and intervention decisions with lasting consequences for individuals. In order to supplement this important area of research, we present a meta-analysis of longitudinal studies investigating the stability of cognitive abilities. The meta-analysis relied on data from 205 longitudinal studies that involved a total of 87,408 participants, resulting in 1,288 test-retest correlation coefficients among manifest variables. For an age of 20 years and a test-retest interval of 5 years, we found a mean rank-order stability of ρ = .76. The effect of mean sample age on stability was best described by a negative exponential function, with low stability in preschool children, rapid increases in stability in childhood, and consistently high stability from late adolescence to late adulthood. This same functional form continued to best describe age trends in stability after adjusting for test reliability. Stability declined with increasing test-retest interval. This decrease flattened out from an interval of approximately 5 years onward. According to the age and interval moderation models, minimum stability sufficient for individual-level diagnostic decisions (rtt = .80) can only be expected over the age of 7 and for short time intervals in children. In adults, stability levels meeting this criterion are obtained for over 5 years. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Why the use of segmented regression analysis to explore change in relations between variables is problematic: A simulation study.

Relations between variables can take different forms like linearity, piecewise linearity, or nonlinearity. Segmented regression analyses (SRA) are specialized statistical methods that detect breaks in the relationship between variables. They are commonly used in the social sciences for exploratory analyses. However, many relations may not be best described by a breakpoint and a resulting piecewise linear relation, but rather by a nonlinearity. In the present simulation study, we examined the application of SRA-specifically the Davies test-in the presence of various forms of nonlinearity. We found that moderate and strong degrees of nonlinearity led to a frequent identification of statistically significant breakpoints and that the identified breakpoints were widely distributed. The results clearly indicate that SRA cannot be used for exploratory analyses. We propose alternative statistical methods for exploratory analyses and outline the conditions for the legitimate use of SRA in the social sciences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Students' intelligence test results after six and sixteen months of irregular schooling due to the COVID-19 pandemic.

The COVID-19 pandemic has affected schooling worldwide. In many places, schools closed for weeks or months, only part of the student body could be educated at any one time, or students were taught online. Previous research discloses the relevance of schooling for the development of cognitive abilities. We therefore compared the intelligence test performance of 424 German secondary school students in Grades 7 to 9 (42% female) tested after the first six months of the COVID-19 pandemic (i.e., 2020 sample) to the results of two highly comparable student samples tested in 2002 (n = 1506) and 2012 (n = 197). The results revealed substantially and significantly lower intelligence test scores in the 2020 sample than in both the 2002 and 2012 samples. We retested the 2020 sample after another full school year of COVID-19-affected schooling in 2021. We found mean-level changes of typical magnitude, with no signs of catching up to previous cohorts or further declines in cognitive performance. Perceived stress during the pandemic did not affect changes in intelligence test results between the two measurements.

Temporal stability and change in manifest intelligence scores: Four complementary analytic approaches.

The temporal stability of psychological test scores is one prerequisite for their practical usability. This is especially true for intelligence test scores. In educational contexts, high stakes decisions with long-term consequences, such as placement in special education programs, are often based on intelligence test results. There are four different types of temporal stability: mean-level change, individual-level change, differential continuity, and ipsative continuity. We present statistical methods for investigating each type of stability. Where necessary, the methods were adapted for the specific challenges posed by intelligence research (e.g., controlling for general intelligence in lower order test scores). We provide step-by-step guidance for the application of the statistical methods and apply them to a real data set of 114 gifted students tested twice with a test-retest interval of 6 months. • Four different types of stability need to be investigated for a full picture of temporal stability in psychological research • Selection and adaption of the methods for the use in intelligence research • Complete protocol of the implementation.

Age and ability differentiation in children: A review and empirical investigation.

Differentiation hypotheses concern changes in the structural organization of cognitive abilities that depend on the level of general intelligence (ability differentiation) or age (developmental differentiation). Part 1 of this article presents a review of the literature on ability and developmental differentiation effects in children, revealing the need for studies that examine both effects simultaneously in this age group with appropriate statistical methods. Part 2 presents an empirical study in which nonlinear factor analytic models were applied to the standardization sample (N = 2,619 German elementary schoolchildren; 48% female; age: M = 8.8 years, SD = 1.2, range 6-12 years) of the THINK 1-4 intelligence test to investigate ability differentiation, developmental differentiation, and their interaction. The sample was nationally representative regarding age, gender, urbanization, and geographic location of residence but not regarding parents' education and migration background (overrepresentation of children with more educated parents, underrepresentation of children with migration background). The results showed no consistent evidence for the presence of differentiation effects or their interaction. Instead, different patterns were observed for figural, numerical, and verbal reasoning. Implications for the construction of intelligence tests, the assessment of intelligence in children, and for theories of cognitive development are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

General intelligence and specific cognitive abilities in adolescence: Tests of age differentiation, ability differentiation, and their interaction in two large samples.

Differentiation of intelligence refers to changes in the structure of intelligence that depend on individuals' level of general cognitive ability (ability differentiation hypothesis) or age (developmental differentiation hypothesis). The present article aimed to investigate ability differentiation, developmental differentiation, and their interaction with nonlinear factor analytic models in 2 studies. Study 1 was comprised of a nationally representative sample of 7,127 U.S. students (49.4% female; Mage = 14.51, SD = 1.42, range = 12.08-17.00) who completed the computerized adaptive version of the Armed Service Vocational Aptitude Battery. Study 2 analyzed the norming sample of the Berlin Intelligence Structure Test with 1,506 German students (44% female; Mage = 14.54, SD = 1.35, range = 10.00-18.42). Results of Study 1 supported the ability differentiation hypothesis but not the developmental differentiation hypothesis. Rather, the findings pointed to age-dedifferentiation (i.e., higher correlations between different abilities with increasing age). There was evidence for an interaction between age and ability differentiation, with greater ability differentiation found for older adolescents. Study 2 provided little evidence for ability differentiation but largely replicated the findings for age dedifferentiation and the interaction between age and ability differentiation. The present results provide insight into the complex dynamics underlying the development of intelligence structure during adolescence. Implications for the assessment of intelligence are discussed. (PsycINFO Database Record (c) 2020 APA, all rights reserved).