Factor structure of intelligence and divergent thinking subtests: A registered report.

Psychologists have investigated creativity for 70 years, and it is now seen as being an important construct, both scientifically and because of its practical value to society. However, several fundamental unresolved problems persist, including a suitable definition of creativity and the ability of psychometric tests to measure divergent thinking-an important component of creativity-in a way that aligns with theory. It is this latter point that this registered report is designed to address. We administered two divergent thinking tests (the verbal and figural versions of the Torrance Tests of Creative Thinking; TTCT) with an intelligence test (the International Cognitive Ability Resource test; ICAR). We then subjected the subscores from these tests to confirmatory factor analysis to examine which of nine theoretically plausible models best fits the data. Results show that none of the pre-registered models fit the data well, an ambiguous result that leaves unanswered the question of whether intelligence and divergent thinking tests measure the same construct. Exploratory (i.e., not pre-registered) measurement models of each test separately shows that the TTCT-F may not measure a coherent, unitary construct-leading to model misspecification when TTCT-F subtests were included in larger models. This study was conducted in accordance with all open science practices, including pre-registration, open data and syntax, and open materials (with the exception of copyrighted and confidential test stimuli). Materials are available at https://osf.io/8rpfz/.

Factor structure of intelligence and divergent thinking subtests: A registered report.

Psychologists have investigated creativity for 70 years, and it is now seen as being an important construct, both scientifically and because of its practical value to society. However, several fundamental unresolved problems persist, including a suitable definition of creativity and the ability of psychometric tests to measure divergent thinking-an important component of creativity-in a way that aligns with theory. It is this latter point that this registered report is designed to address. We propose to administer two divergent thinking tests (the verbal and figural versions of the Torrance Tests of Creative Thinking; TTCT) with an intelligence test (the International Cognitive Ability Resource test; ICAR). We will then subject the subscores from these tests to confirmatory factor analysis to test which of nine theoretically plausible models best fits the data. When this study is completed, we hope to better understand whether the degree to which the TTCT and ICAR measure distinct constructs. This study will be conducted in accordance with all open science practices, including pre-registration, open data and syntax, and open materials (with the exception of copyrighted and confidential test stimuli).

Stephen Jay Gould's Analysis of the Army Beta Test in The Mismeasure of Man: Distortions and Misconceptions Regarding a Pioneering Mental Test.

In The Mismeasure of Man, Stephen Jay Gould argued that the preconceived beliefs and biases of scientists influence their methods and conclusions. To show the potential consequences of this, Gould used examples from the early days of psychometrics and allied fields, arguing that inappropriate assumptions and an elitist desire to rank individuals and/or groups produced incorrect results. In this article, we investigate a section of The Mismeasure of Man in which Gould evaluated the Army Beta intelligence test for illiterate American draftees in World War I. We evaluated Gould's arguments that the Army Beta (a) had inappropriate content, (b) had unsuitable administration conditions, (c) suffered from short time limits, and (d) could not have measured intelligence. By consulting the historical record and conducting a pre-registered replication of Gould's administration of the test to a sample of college students, we show that Gould mischaracterized the Army Beta in a number of ways. Instead, the Army Beta was a well-designed test by the standards of the time, and all evidence indicates that it measured intelligence a century ago and can, to some extent, do so today.

Spearman's g found in 31 non-Western nations: Strong evidence that g is a universal phenomenon.

Spearman's g is the name for the shared variance across a set of intercorrelating cognitive tasks. For some-but not all-theorists, g is defined as general intelligence. While g is robustly observed in Western populations, it is questionable whether g is manifested in cognitive data from other cultural groups. To test whether g is a cross-cultural phenomenon, we searched for correlation matrices or data files containing cognitive variables collected from individuals in non-Western, nonindustrialized nations. We subjected these data to exploratory factor analysis (EFA) using promax rotation and 2 modern methods of selecting the number of factors. Samples that produced more than 1 factor were then subjected to a second-order EFA using the same procedures and a Schmid-Leiman solution. Across 97 samples from 31 countries totaling 52,340 individuals, we found that a single factor emerged unambiguously from 71 samples (73.2%) and that 23 of the remaining 26 samples (88.5%) produced a single second-order factor. The first factor in the initial EFA explained an average of 45.9% of observed variable variance (SD = 12.9%), which is similar to what is seen in Western samples. One sample that produced multiple second-order factors only did so with 1 method of selecting the number of factors in the initial EFA; the alternate method of selecting the number of factors produced a single higher-order factor. Factor extraction in a higher-order EFA was not possible in 2 samples. These results show that g appears in many cultures and is likely a universal phenomenon in humans. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Possible economic benefits of full-grade acceleration.

Full-grade acceleration is an intervention in which students finish the K-12 curriculum at least one year early, usually due to early entrance to kindergarten, grade skipping, or early graduation from high school. Many studies have shown benefits during childhood for accelerated individuals, but few studies have examined outcomes of acceleration in adulthood. In this study data from five longitudinal datasets were combined to compare adult incomes of accelerated and non-accelerated subjects after controlling for five important childhood covariates. Results showed that accelerated adults earned 4.66% more per year (d=0.044). Income differences between accelerated and non-accelerated groups were larger for women than men. A conservative estimate is that there is a $72,000 lifetime earnings difference between accelerated and non-accelerated subjects, though this study cannot show a causal association between acceleration and increased income.

A Biopsychosocial Examination of ATOD Use among Middle and High School Students.

OBJECTIVE: To examine Indiana middle and high school students' use of 17 licit and illicit substances using item response theory to produce theta scores to identify sociodemographics, psychological factors, and normative beliefs associated with life-time drug use. METHODS: Cross-sectional data from 1233 students were examined. Theta scores were calculated across 17 substances using 2PL item response theory modeling. General least squares regressions were performed. RESULTS: Those perceiving their peers/parents approved substance use and those reporting worse worry control had higher theta scores. Those perceiving the risks of drug use outweighed the benefits and conforming less to negative influences had significantly lower theta scores. CONCLUSIONS: Findings support the utility of the Biopsychosocial Model to examine lifetime drug use and the severity of substances used among adolescents simultaneously.

Exploring the various interpretations of "test bias".

Test bias is a hotly debated topic in society, especially as it relates to diverse groups of examinees who often score low on standardized tests. However, the phrase "test bias" has a multitude of interpretations that many people are not aware of. In this article, we explain five different meanings of "test bias" and summarize the empirical and theoretical evidence related to each interpretation. The five meanings are as follows: (a) mean group differences, (b) differential predictive validity, (c) differential item functioning, (d) differing factor structures of tests, and (e) unequal consequences of test use for various groups. We explain in this article why meanings (a) and (e) are not actual forms of test bias and that there are serious concerns about (b). In our conclusion, we discuss the benefits of standardized testing for diverse examinees and urge readers to be careful and precise in their use of the phrase "test bias."

What the Joint Admission Medical Program (JAMP) can do for Texas physicians; what Texas physicians can do for JAMP.

Texas faces health challenges requiring a physician workforce with understanding of a broad range of issues -- including the role of culture, income level, and health beliefs -- that affect the health of individuals and communities. Building on previous successful physician workforce "pipeline" efforts, Texas established the Joint Admission Medical Program (JAMP), a first-of-its-kind program to encourage access to medical education by Texans who are economically disadvantaged. The program benefits those from racial and ethnic minority groups and involves all 31 public and 34 private Texas undergraduate colleges and universities offering life science degrees, as well as all 9 medical schools. Available program data indicate that JAMP has broadened enrollment diversity in Texas' medical schools. However, greater progress requires strengthened partnerships with professional colleagues practicing medicine in communities across Texas. This article explores how JAMP can help Texas physicians and how Texas physicians can help JAMP.

Managing clustered data using hierarchical linear modeling.

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence assumption and lead to correct analysis of data, yet it is rarely used in nutrition research. The purpose of this viewpoint is to illustrate the benefits of hierarchical linear modeling within a nutrition research context.

An introduction to item response theory for health behavior researchers.

OBJECTIVE: To introduce item response theory (IRT) to health behavior researchers by contrasting it with classical test theory and providing an example of IRT in health behavior. METHOD: Demonstrate IRT by fitting the 2PL model to substance-use survey data from the Adolescent Health Risk Behavior questionnaire (n=1343 adolescents). RESULTS: An IRT 2PL model can produce viable substance use scores that differentiate different levels of substance use, resulting in improved precision and specificity at the respondent level. CONCLUSION: IRT is a viable option for health researchers who want to produce high-quality scores for unidimensional constructs. The results from our example-although not flawless-demonstrate the feasibility of IRT in health behavior research.

Estimating confidence intervals for eigenvalues in exploratory factor analysis.

Exploratory factor analysis (EFA) has become a common procedure in educational and psychological research. In the course of performing an EFA, researchers often base the decision of how many factors to retain on the eigenvalues for the factors. However, many researchers do not realize that eigenvalues, like all sample statistics, are subject to sampling error, which means that confidence intervals (CIs) can be estimated for each eigenvalue. In the present article, we demonstrate two methods of estimating CIs for eigenvalues: one based on the mathematical properties of the central limit theorem, and the other based on bootstrapping. References to appropriate SAS and SPSS syntax are included. Supplemental materials for this article may be downloaded from http://brm.psychonomic-journals.org/content/supplemental.