A Factorial Study of Experimental Tests of Integration, Judgment, and Planning

Lucas, Charles M.; French, John W.

doi:10.1002/j.2333-8504.1953.tb00231.x

Cited by 6 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This left two other datasets for which the bifactor and higher-order models could be compared using FOFC. In the Lucas and French [56] dataset, all of the fit statistics favored the higher-order model over the bifactor model. In the Thurstone and Thurstone [8] dataset, the Δχ 2 test, NFI, and CFI indicated that the bifactor model had better fit, and TLI, RMSEA, and AIC indicated that the higher-order model had better fit.…”

Section: Resultsmentioning

confidence: 99%

The Bifactor Model Fits Better Than the Higher-Order Model in More Than 90% of Comparisons for Mental Abilities Test Batteries

Cucina

Byle

2017

J. Intell.

View full text Add to dashboard Cite

Abstract:The factor structure of mental abilities has most often been depicted using a higher-order model. Under this model, general mental ability (g) is placed at the top of a pyramid, with "loading" arrows going from it to the other factors of intelligence, which in turn go to subtest scores. In contrast, under the bifactor model (also known as the nested factors/direct hierarchical model), each subtest score has its own direct loading on g; the non-g factors (e.g., the broad abilities) do not mediate the relationships of the subtest scores with g. Here we summarized past research that compared the fit of higher-order and bifactor models using confirmatory factor analysis (CFA). We also analyzed additional archival datasets to compare the fit of the two models. Using a total database consisting of 31 test batteries, 58 datasets, and 1,712,509 test takers, we found stronger support for a bifactor model of g than for the traditional higher-order model. Across 166 comparisons, the bifactor model had median increases of 0.076 for the Comparative Fit Index (CFI), 0.083 for the Tucker-Lewis Index (TLI), and 0.078 for the Normed Fit Index (NFI) and decreases of 0.028 for the root mean square error of approximation (RMSEA) and 1343 for the Akaike Information Criterion (AIC). Consequently, researchers should consider using bifactor models when conducting CFAs. The bifactor model also makes the unique contributions of g and the broad abilities to subtest scores more salient to test users.

show abstract

Section: Resultsmentioning

confidence: 99%

The Bifactor Model Fits Better Than the Higher-Order Model in More Than 90% of Comparisons for Mental Abilities Test Batteries

Cucina

Byle

2017

J. Intell.

View full text Add to dashboard Cite

show abstract

“…Symbol Recognition is a variety of Associative Memory usually measured by such a test as Picture-Number (French, 1954, p. 15). Beyond these two familiar factors, we found it necessary to identify another which is not so well known, called Integration I (Guilford & Lacey, 1947;Lucas & French, 1953). In its simplest form, it appears to be the capability of "holding in mind" several operations in sequence, and is often measured by tests of following directions.…”

Section: Analysis Of the Taskmentioning

confidence: 99%

Abilities and learning sets in knowledge acquisition.

Gagné¹,

Paradise²

1961

Psychological Monographs: General and Applied

162

View full text Add to dashboard Cite

“…This test was developed to measure a factor which was called Integration (Guilford & Lacey, 1947). It was shown to measure an integration factor successfully (Lucas & French, 1953), and it had encouraging validity in the CEEB validity study (French, 1958). The task is to follow complex and interconnecting rules in order to solve problems.…”

Section: Sample Itemsmentioning

confidence: 98%

New tests for predicting the performance of college students with high-level aptitude.

French¹

1964

Journal of Educational Psychology

Self Cite

View full text Add to dashboard Cite

Fifteen experimental tests were tried out in an attempt to improve the capacity of the College Board tests to predict the college performance of students in very high-level colleges. The tests were intended to challenge such students in a way that a mere increase in the difficulty of present verbal and mathematical tests probably could not do. The experimental tests include tests of reasoning, information, integration, fluency, memory, and other qualities. The validities of the tests for freshman grades were averaged across colleges. Multiple correlations showed that a meaningful increase in the validity of present tests and high-school rank could be obtained by substituting reasoning and information items for parts of the present mathematical and verbal tests. 1 These three tests and the first one in Book 2 were developed by S. Myers of the Test Development Division, Educational Testing Service, Princeton, N. J.* In all sample items, the correct answer is given in italics.

show abstract

A Factorial Study of Experimental Tests of Integration, Judgment, and Planning

Cited by 6 publications

References 1 publication

The Bifactor Model Fits Better Than the Higher-Order Model in More Than 90% of Comparisons for Mental Abilities Test Batteries

The Bifactor Model Fits Better Than the Higher-Order Model in More Than 90% of Comparisons for Mental Abilities Test Batteries

Abilities and learning sets in knowledge acquisition.

New tests for predicting the performance of college students with high-level aptitude.

Contact Info

Product

Resources

About