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This study proposes a procedure for substantive dimensionality estimation in the presence of wording effects, the inconsistent response to regular and reversed self-report items. The procedure developed consists of subtracting an approximate estimate of the wording effects variance from the sample correlation matrix and then estimating the substantive dimensionality on the residual correlation matrix. This is achieved by estimating a random intercept factor with unit loadings for all the regular and unrecoded reversed items. The accuracy of the procedure was evaluated through an extensive simulation study that manipulated nine relevant variables and employed the exploratory graph analysis (EGA) and parallel analysis (PA) retention methods. The results indicated that combining the proposed procedure with EGA or PA achieved high accuracy in estimating the substantive latent dimensionality, but that EGA was superior. Additionally, the present findings shed light on the complex ways that wording effects impact the dimensionality estimates when the response bias in the data is ignored. A tutorial on substantive dimensionality estimation with the R package EGAnet is offered, as well as practical guidelines for applied researchers. [ABSTRACT FROM AUTHOR]

Exploratory bi-factor analysis (EBFA) is a very popular approach to estimate models where specific factors are concomitant to a single, general dimension. However, the models typically encountered in fields like personality, intelligence, and psychopathology involve more than one general factor. To address this circumstance, we developed an algorithm (GSLiD) based on partially specified targets to perform exploratory bi-factor analysis with multiple general factors (EBFA-MGF). In EBFA-MGF, researchers do not need to conduct independent bi-factor analyses anymore because several bi-factor models are estimated simultaneously in an exploratory manner, guarding against biased estimates and model misspecification errors due to unexpected cross-loadings and factor correlations. The results from an exhaustive Monte Carlo simulation manipulating nine variables of interest suggested that GSLiD outperforms the Schmid-Leiman approximation and is robust to challenging conditions involving cross-loadings and pure items of the general factors. Thereby, we supply an R package (bifactor) to make EBFA-MGF readily available for substantive research. Finally, we use GSLiD to assess the hierarchical structure of a reduced version of the Personality Inventory for DSM-5 Short Form (PID-5-SF). [ABSTRACT FROM AUTHOR]

The use of multidimensional forced-choice questionnaires has been proposed as a means of improving validity in the assessment of non-cognitive attributes in high-stakes scenarios. However, the reduced precision of trait estimates in this questionnaire format is an important drawback. Accordingly, this article presents an optimization procedure for assembling pairwise forced-choice questionnaires while maximizing posterior marginal reliabilities. This procedure is performed through the adaptation of a known genetic algorithm (GA) for combinatorial problems. In a simulation study, the efficiency of the proposed procedure was compared with a quasi-brute-force (BF) search. For this purpose, five-dimensional item pools were simulated to emulate the real problem of generating a forced-choice personality questionnaire under the five-factor model. Three factors were manipulated: (1) the length of the questionnaire, (2) the relative item pool size with respect to the questionnaire's length, and (3) the true correlations between traits. The recovery of the person parameters for each assembled questionnaire was evaluated through the squared correlation between estimated and true parameters, the root mean square error between the estimated and true parameters, the average difference between the estimated and true inter-trait correlations, and the average standard error for each trait level. The proposed GA offered more accurate trait estimates than the BF search within a reasonable computation time in every simulation condition. Such improvements were especially important when measuring correlated traits and when the relative item pool sizes were higher. A user-friendly online implementation of the algorithm was made available to the users. [ABSTRACT FROM AUTHOR]

The new methodological and technological developments of the last decade make it possible to resolve or, at least, attenuate the psychometric problems of forced-choice (FC) tests for the measurement of personality. In these tests, the person being tested is shown blocks of two or more sentences of similar social desirability, from which he or she must choose which one best represents him or her. Thus, FC tests aim to reduce response bias in self-report questionnaires. However, their use is not without risks and complications if they are not created properly. Fortunately, new psychometric models make it possible to model responses in this type of test and to optimize their construction. Moreover, they allow the construction of "on the fly" computerized adaptive FC tests (CAT-FC), in which each item is constructed on the spot, optimally matching sentences from a previously calibrated bank. [ABSTRACT FROM AUTHOR]

As general factor modeling continues to grow in popularity, researchers have become interested in assessing how reliable general factor scores are. Even though omega hierarchical estimation has been suggested as a useful tool in this context, little is known about how to approximate it using modern bi-factor exploratory factor analysis methods. This study is the first to compare how omega hierarchical estimates were recovered by six alternative algorithms: Bi-quartimin, bi-geomin, Schmid-Leiman (SL), empirical iterative empirical target rotation based on an initial SL solution (SLiD), direct SL (DSL), and direct bi-factor (DBF). The algorithms were tested in three Monte-Carlo simulations including bi-factor and second-order structures and presenting complexities such as cross-loadings or pure indicators of the general factor and structures without a general factor. Results showed that SLiD provided the best approximation to omega hierarchical under most conditions. Overall, neither SL, bi-quartimin, nor bi-geomin produced an overall satisfactory recovery of omega hierarchical. Lastly, the performance of DSL and DBF depended upon the average discrepancy between the loadings of the general and the group factors. The re-analysis of eight classical datasets further illustrated how algorithm selection could influence judgments regarding omega hierarchical. [ABSTRACT FROM AUTHOR]

Background: The inclusion of direct and reversed items in scales is a commonly-used strategy to control acquiescence bias. However, this is not enough to avoid the distortions produced by this response style in the structure of covariances and means of the scale in question. This simulation study provides evidence on the performance of two different procedures for modelling the influence of acquiescence bias on partially balanced multidimensional scales: a method based on exploratory factor analysis (EFA) with target rotation, and a method based on random intercept factor analysis (RIFA). Method: The independent variables analyzed in a simulation study were sample size, number of items per factor, balance of substantive loadings of direct and reversed items, size and heterogeneity of acquiescence loadings, and inter-factor correlation. Results: The RIFA method had better performance over most of the conditions, especially for the balanced conditions, although the variance of acquiescence factor loadings had a certain impact. In relation to the EFA method, it was severely affected by a low degree of balance. Conclusions: RIFA seems the most robust approach, but EFA also remains a good alternative for medium and fully balanced scales. [ABSTRACT FROM AUTHOR]

Multidimensional forced-choice questionnaires are widely regarded in the personnel selection literature for their ability to control response biases. Recently developed IRT models usually rely on the assumption that item parameters remain invariant when they are paired in forced-choice blocks, without giving it much consideration. This study aims to test this assumption empirically on the MUPP-2PL model, comparing the parameter estimates of the forced-choice format to their graded-scale equivalent on a Big Five personality instrument. The assumption was found to hold reasonably well, especially for the discrimination parameters. In the cases in which it was violated, we briefly discuss the likely factors that may lead to non-invariance. We conclude discussing the practical implications of the results and providing a few guidelines for the design of forced-choice questionnaires based on the invariance assumption. [ABSTRACT FROM AUTHOR]

Abstract Here we test the developmental theory of sex differences in intelligence using latent modeling. The theory has been recently updated (Lynn, 2017). Based on men's greater average brain volumes and premature maturation in women, the theory predicts an intelligence advantage for women (or null sex differences) in early adolescence, but an advantage for men in late adolescence. The findings reported by Lynn are consistent with the theory, but basic measurement issues were not met. Are we taping the same construct regardless of sex and age and can we provide sound conclusions? We considered 10,335 individuals (4992 boys and 5343 girls) within an age range of 12–18 years. They completed the subtests included in the TEA Ability Battery (BAT-7). Theta scores for each subtest were estimated using a three-parameter logistic Item Response Theory model (3PL IRT). Results fitted properly to invariance criteria across age and sex. Latent estimates for the general factor of intelligence (g) were used for testing the theory. The observed findings were in agreement with the developmental theory: there were null sex differences at 12 years of age, but there was an average difference favoring boys equivalent to 5 IQ points at 18 years of age. Highlights • We test the developmental theory of sex differences in intelligence. • 4992 boys and 5343 girls within an age range of 12–18 years were considered. • Latent estimates of general intelligence (g) were used for testing the theory. • There were null sex differences at 12 years of age. • There was an average difference favoring boys of 5 IQ points at 18 years of age. [ABSTRACT FROM AUTHOR]

Contemporary models of personality assume a hierarchical structure in which broader traits contain narrower traits. Individual differences in response styles also constitute a source of score variance. In this study, the bifactor model is applied to separate these sources of variance for personality subscores. The procedure is illustrated using data for two personality inventories—NEO Personality Inventory–Revised and Zuckerman–Kuhlman–Aluja Personality Questionnaire. The inclusion of the acquiescence method factor generally improved the fit to acceptable levels for the Zuckerman–Kuhlman–Aluja Personality Questionnaire, but not for the NEO Personality Inventory–Revised. This effect was higher in subscales where the number of direct and reverse items is not balanced. Loadings on the specific factors were usually smaller than the loadings on the general factor. In some cases, part of the variance was due to domains being different from the main one. This information is of particular interest to researchers as they can identify which subscale scores have more potential to increase predictive validity. [ABSTRACT FROM AUTHOR]

Multidimensional computerized adaptive testing based on the bifactor model (MCAT-B) can provide efficient assessments of multifaceted constructs. In this study, MCAT-B was compared with a short fixed-length scale and computerized adaptive testing based on unidimensional (UCAT) and multidimensional (correlated-factors) models (MCAT) to measure the Big Five model of personality. The sample comprised 826 respondents who completed a pool with 360 personality items measuring the Big Five domains and facets. The dimensionality of the Big Five domains was also tested. With only 12 items per domain, the MCAT and MCAT-B procedures were more efficient to assess highly multidimensional constructs (e.g., Agreeableness), whereas no differences were found with UCAT and the short scale with traits that were essentially unidimensional (e.g., Extraversion). Furthermore, the study showed that MCAT and MCAT-B provide better content-balance of the pool because, for each Big Five domain, items from all the facets are selected in similar proportions. (PsycINFO Database Record (c) 2018 APA, all rights reserved). [ABSTRACT FROM AUTHOR]

Abstract Different models might explain one the most replicated findings in Psychology, namely, the positive correlation among diverse tests of cognitive ability (positive manifold). The g factor and the mutualism models are examples. Mutualism suggests that the manifold emerges progressively during development, as a consequence of interactions among originally uncorrelated cognitive process. The g factor model departs from this perspective and assumes that there is an underlying latent factor remaining fairly constant across development. The present study investigates these two approaches considering 661 children (age range = 6 to 12 years) recruited from primary school in Tehran. A wide set of cognitive tests, selected under the CHC framework, was completed by these individuals. First, the measurement model was tested across age for demonstrating that the factor of interest is properly tapped by the administered measures. Afterwards, the scores were submitted to statistical analyses for testing the models' prediction: the mutualism approach predicts stronger correlations among scores as individuals grow up, whereas the g model does not. Results revealed metric invariance regarding the obtained g factor across the age range. Furthermore, the amount of variance explained by this factor remained fairly constant. In conclusion, the findings were consistent with the g model. Highlights • The g factor and the mutualism models were tested using cross-sectional data. • 661 children (age range = 6 to 12 years) were recruited from primary school in Tehran. • A wide set of cognitive tests, selected under the CHC framework, was administered. • The findings were consistent with the g model. [ABSTRACT FROM AUTHOR]

Purpose: Developing valid and reliable instruments that can be used across countries is necessary. The present study aimed to test the comparability of quality of life scores across three European countries (Finland, Poland, and Spain).Method: Data from 9987 participants interviewed between 2011 and 2012 were employed, using nationally representative samples from the Collaborative Research on Ageing in Europe project. The WHOQOL-AGE questionnaire is a 13-item test and was employed to assess the quality of life in the three considered countries. First of all, two models (a bifactor model and a two-correlated factor model) were proposed and tested in each country by means of confirmatory factor models. Second, measurement invariance across the three countries was tested using multi-group confirmatory factor analysis for that model which showed the best fit. Finally, differences in latent mean scores across countries were analyzed.Results: The results indicated that the bifactor model showed more satisfactory goodness-of-fit indices than the two-correlated factor model and that the WHOQOL-AGE questionnaire is a partially scalar invariant instrument (only two items do not meet scalar invariance). Quality of life scores were higher in Finland (considered as the reference category: mean = 0, SD = 1) than in Spain (mean = - 0.547, SD = 1.22) and Poland (mean = - 0.927, SD = 1.26).Conclusions: Respondents from Finland, Poland, and Spain attribute the same meaning to the latent construct studied, and differences across countries can be due to actual differences in quality of life. According to the results, the comparability across the different considered samples is supported and the WHOQOL-AGE showed an adequate validity in terms of cross-country validation. Caution should be exercised with the two items which did not meet scalar invariance, as potential indicator of differential item functioning. [ABSTRACT FROM AUTHOR]

Research related to the fit evaluation at the item level involving cognitive diagnosis models (CDMs) has been scarce. According to the parsimony principle, balancing goodness of fit against model complexity is necessary. General CDMs require a larger sample size to be estimated reliably, and can lead to worse attribute classification accuracy than the appropriate reduced models when the sample size is small and the item quality is poor, which is typically the case in many empirical applications. The main purpose of this study was to systematically examine the statistical properties of four inferential item-fit statistics: S-[sup X2], the likelihood ratio (LR) test, the Wald (W) test, and the Lagrange multiplier (LM) test. To evaluate the performance of the statistics, a comprehensive set of factors, namely, sample size, correlational structure, test length, item quality, and generating model, is systematically manipulated using Monte Carlo methods. Results show that the S-[sup X2] statistic has unacceptable power. Type I error and power comparisons favor LR and W tests over the LM test. However, all the statistics are highly affected by the item quality. With a few exceptions, their performance is only acceptable when the item quality is high. In some cases, this effect can be ameliorated by an increase in sample size and test length. This implies that using the above statistics to assess item fit in practical settings when the item quality is low remains a challenge. [ABSTRACT FROM AUTHOR]

Background: Even though the Five Factor Model (FFM) has been the dominant paradigm in personality research for the past two decades, very few studies have measured the FFM adaptively. Thus, the purpose of this research was the building of a new item pool to develop a computerized adaptive test (CAT) for personality assessment. Method: A pool of 480 items that measured the FFM facets was developed and applied to 826 participants. Facets were calibrated separately and item selection was performed being mindful of the preservation of unidimensionality of each facet. Then, a post-hoc simulation study was carried out to test the performance of separate CATs to measure the facets. Results: The final item pool was composed of 360 items with good psychometric properties. Findings reveal that a CAT administration of four items per facet (total length of 120 items) provides accurate facets scores, while maintaining the factor structure of the FFM. Conclusions: An item pool with good psychometric properties was obtained and a CAT simulation study demonstrated that the FFM facets could be measured with precision using a third of the items in the pool. [ABSTRACT FROM AUTHOR]

The current study proposes a newbi-factor rotationmethod, Schmid-Leiman with iterative target rotation (SLi), based on the iteration of partially specified target matrices and an initial target constructed from a Schmid-Leiman (SL) orthogonalization. SLi was expected to ameliorate some of the limitations of the previously presented SL bi-factor rotations, SL and SL with target rotation (SLt), when the factor structure either includes cross-loadings, near-zero loadings, or both. AMonte Carlo simulationwas carried out to test the performance of SLi, SL, SLt, and the two analytic bi-factor rotations, bi-quartimin and bi-geomin. The results revealed that SLi accurately recovered the bi-factor structures across the majority of the conditions, and generally outperformed the other rotation methods. SLi provided the biggest improvements over SL and SLt when the bi-factor structures contained cross-loadings and pure indicators of the general factor. Additionally, SLi was superior to bi-quartimin and bi-geomin, which performed inconsistently across the types of factor structures evaluated. No method produced a good recovery of the bi-factor structures when small samples (N = 200) were combined with low factor loadings (0.30-0.50) in the specific factors. Thus, it is recommended that larger samples of at least 500 observations be obtained. [ABSTRACT FROM AUTHOR]

IQ summary scores may not involve equivalent psychological meaning for different educational levels. Ultimately, this relates to the distinction between constructs and measurements. Here, we explore this issue studying the standardization of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) for Spain. A representative sample of 743 individuals (374 females and 369 males) who completed the 15 subtests comprising this intelligence battery was considered. We analyzed (a) the best latent factor structure for modeling WAIS-IV subtest performance, (b) measurement invariance across educational levels, and (c) the relationships of educational level/attainment with latent factors, Full Scale IQ (FSIQ), and index factor scores. These were the main findings: (a) the bifactor model provides the best fit; (b) there is partial invariance, and therefore it is concluded that the battery is a proper measure of the constructs of interest for the educational levels analyzed (nevertheless, the relevance of g decreases at high educational levels); (c) at the latent level, g and, to a lesser extent, Verbal Comprehension and Processing Speed, are positively related to educational level/attainment; (d) despite the previous finding, we find that Verbal Comprehension and Processing Speed factor index scores have reduced incremental validity beyond FSIQ; and (e) FSIQ is a slightly biased measure of g. (PsycINFO Database Record [ABSTRACT FROM AUTHOR]

Previous research has suggested multiple factor structures for the 12-item General Health Questionnaire (GHQ-12), with contradictory evidence arising across different studies on the validity of these models. In the present research, it was hypothesized that these inconsistent findings were due to the interaction of 3 main methodological factors: ambiguous response categories in the negative items, multiple scoring schemes, and inappropriate estimation methods. Using confirmatory factor analysis with appropriate estimation methods and scores obtained from a large (n = 27,674) representative Spanish sample, we tested this hypothesis by evaluating the fit and predictive validities of 4 GHQ-12 factor' models- unidimensional, Hankins' (2008a) response bias model, Andrich and Van Schoubroeck's (1989) 2-factor model, and Graetz's (1991) 3-factor model-across 3 scoring methods: standard, corrected, and Likert. In addition, the impact of method effects on the reliability of the global GHQ-12 scores was also evaluated. The combined results of this study support the view that the GHQ-12 is a unidimensional measure that contains spurious multidimensionality under certain scoring schemes (corrected and Likert) as a result of ambiguous response categories in the negative items. Therefore, it is suggested that the items be scored using the standard method and that only a global score be derived fronfthe instrument. [ABSTRACT FROM AUTHOR]

Intelligence is composed of a set of cognitive abilities hierarchically organized. General and specific abilities capture distinguishable, but related, facets of the intelligence construct. Here, we analyze gray matter with three morphometric indices (volume, cortical surface area, and cortical thickness) at three levels of the intelligence hierarchy (tests, first-order factors, and a higher-order general factor, g). A group of one hundred and four healthy young adults completed a cognitive battery and underwent high-resolution structural MRI. Latent scores were computed for the intelligence factors and tests were also analyzed. The key finding reveals substantial variability in gray matter correlates at the test level, which is substantially reduced for the first-order and the higher-order factors. This supports a reversed hierarchy in the brain with respect to cognitive abilities at different psychometric levels: the greater the generality, the smaller the number of relevant gray matter clusters accounting for individual differences in intelligent performance. Hum Brain Mapp 35:3805-3818, 2014. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: The present study investigates the simultaneous relationship among short-term memory (STM), working memory capacity (WMC), executive function (EF) and fluid intelligence (Gf) across two age groups using multi-group confirmatory factor analysis (MG-CFA). A total of 356 children recruited from primary school in Tehran were tested. Gf was assessed by the four subtests of the Cattell Culture Fair Intelligence Test. Digit Span, Letter Span, and the Kim Karad Visual Memory Test were used for measuring STM. WMC was measured by Backward Digit Span, Backward Letter Span, and Counting Span. Finally, the Stroop Task, the Wisconsin Card Sorting Test, and the Keep Track task measured EF. The key results derived from the analysis of the considered four-way relationships showed that STM did predict individual differences in Gf for both age groups with the same regression value. Furthermore, the contribution of specific WMC and EF variance (with their STM component removed) changed across age demonstrating a substantial instability for these constructs. [Copyright &y& Elsevier]

Abstract: Here the simultaneous relationships among cognitive ability (CA), past academic failure (PAF), future academic aspirations (FAA), and present scholastic achievement (PSA) were investigated. For addressing these rarely considered relations, two independent representative samples comprising 2796 students were analyzed; the first sample (young adolescents) included 1695 students from the third cycle of elementary school, whereas the second sample (old adolescents) comprised 1101 students from secondary school. SEM (structural equation model) analyses were computed and the main findings revealed that (1) CA, PAF, and FAA predict PSA, (2) CA is the best predictor of PSA, and (3) excluding PAF and FAA from the final SEM model produces a substantial reduction in the achieved predictive validity, especially for Language. [Copyright &y& Elsevier]

Abstract: The analysis of sex differences in cognitive abilities is largely confusing because these differences are masked by the pervasive influence of the general factor of intelligence (g). In this study a battery of five reasoning tests (abstract [AR], numerical [NR], verbal [VR], mechanical [MR], and spatial [SR]) was completed by a sample of 3233 young and old adolescents representative of the population. Using a latent variable approach, mean differences on the general factor were estimated after examining measurement invariance. Results show that the difference, favoring boys in latent g increases with age from two to four IQ points. Further, boys outperform girls in all the subtests and the observed differences were generally explained by g. However, mechanical reasoning is a systematic and strong exception to this finding. For the young adolescents, the observed difference in MR is equivalent to 10 IQ points, and this difference increases to 13 IQ points for the old adolescents. Only 1 (young) or 2 (old) IQ points of the sex difference in MR can be accounted for by g. The findings suggest that the persistent – and usually neglected average large advantage of boys in mechanical reasoning (MR) — orthogonal to g – might be behind their higher presence in STEM (science, technology, engineering, and math) disciplines. A new look at this relevant social issue is proposed in this study. [Copyright &y& Elsevier]

Multidimensional forced-choice (FC) questionnaires have been consistently found to reduce the effects of socially desirable responding and faking in noncognitive assessments. Although FC has been considered problematic for providing ipsative scores under the classical test theory, item response theory (IRT) models enable the estimation of nonipsative scores from FC responses. However, while some authors indicate that blocks composed of opposite-keyed items are necessary to retrieve normative scores, others suggest that these blocks may be less robust to faking, thus impairing the assessment validity. Accordingly, this article presents a simulation study to investigate whether it is possible to retrieve normative scores using only positively keyed items in pairwise FC computerized adaptive testing (CAT). Specifically, a simulation study addressed the effect of (a) different bank assembly (with a randomly assembled bank, an optimally assembled bank, and blocks assembled on-the-fly considering every possible pair of items), and (b) block selection rules (i.e., T, and Bayesian D and A -rules) over the estimate accuracy and ipsativity and overlap rates. Moreover, different questionnaire lengths (30 and 60) and trait structures (independent or positively correlated) were studied, and a nonadaptive questionnaire was included as baseline in each condition. In general, very good trait estimates were retrieved, despite using only positively keyed items. Although the best trait accuracy and lowest ipsativity were found using the Bayesian A -rule with questionnaires assembled on-the-fly, the T -rule under this method led to the worst results. This points out to the importance of considering both aspects when designing FC CAT. [ABSTRACT FROM AUTHOR]

Despite strong evidence supporting the use of Velicer’s minimum average partial (MAP) method to establish the dimensionality of continuous variables, little is known about its performance with categorical data. Seeking to fill this void, the current study takes an in-depth look at the performance of the MAP procedure in the presence of ordinal-level measurement. Using Monte Carlo methods, seven factors related to the data (sample size, factor loading, number of variables per factor, number of factors, factor correlation, number of response categories, and skewness) as well as two factors related to the MAP method (type of correlation matrix and power) were systematically manipulated. The results indicate that using polychoric correlations and the squared partial correlations leads to considerably more accurate estimations than using Pearson correlations and/or raising the partial correlations to the fourth power. Additionally, the MAP method is shown to be a biased estimator of dimensionality in two conditions: (a) for low factor loadings (.40) and (b) for medium factor loadings (.55) and a small number of variables per factor (≤ 6). The applicability of this method with categorical variables is discussed in the context of these findings. [ABSTRACT FROM PUBLISHER]

This article deals with some of the problems that have hindered the application of Samejima's and Thissen and Steinberg's multiple-choice models: (a) parameter estimation difficulties owing to the large number of parameters involved, (b) parameter identifiability problems in the Thissen and Steinberg model, and (c) their treatment of omitted responses. The authors propose a new multiple-choice model (Restricted Samejima Multiple-Choice Model) that is more explicit about the assumed omitting mechanisms and takes advantage of this knowledge to improve the estimation of parameters. The three above-mentioned models and the Nominal Response Model were fitted to a 3,224-subject sample that took a Written English Test. Fit plots, X 2 statistics, and information-based fit indexes were obtained to assess the goodness of fit. Results show that the new model proposed fits as well as the other two multiple-choice models and better than the Nominal model. A parameter recovery simulation study was also carried out to confirm that its estimation features are indeed improved. Parameters are better recovered in the new model than in the other two multiple-choice models. [ABSTRACT FROM PUBLISHER]

Abstract: Working memory and the general factor of intelligence (g) are highly related constructs. However, we still don''t know why. Some models support the central role of simple short-term storage, whereas others appeal to executive functions like the control of attention. Nevertheless, the available empirical evidence does not suffice to get an answer, presumably because relevant measures are frequently considered in isolation. To overcome this problem, here we consider concurrently simple short-term storage, mental speed, updating, and the control of attention along with working memory and intelligence measures, across three separate studies. Several diverse measures are administered to a total of 661 participants. The findings are consistent with the view that simple short-term storage largely accounts for the relationship between working memory and intelligence. Mental speed, updating, and the control of attention are not consistently related to working memory, and they are not genuinely associated with intelligence once the short-term storage component is removed. [Copyright &y& Elsevier]

Abstract: There are several studies showing that working memory and intelligence are strongly related. However, working memory tasks require simultaneous processing and storage, so the causes of their relationship with intelligence are currently a matter of discussion. The present study examined the simultaneous relationships among short-term memory (STM), working memory (WM), and general intelligence (g). Two hundred and eight participants performed six verbal, quantitative, and spatial STM tasks, six verbal, quantitative, and spatial WM tasks, and eight tests measuring fluid, crystallized, spatial, and quantitative intelligence. Especial care is taken to avoid misrepresenting the relations among the constructs being studied because of specific task variance. Structural equation modelling (SEM) results revealed that (a) WM and g are (almost) isomorphic constructs, (b) the isomorphism vanishes when the storage component of WM is partialed out, and (c) STM and WM (with its storage component partialed out) predict g. [Copyright &y& Elsevier]

There are no sex differences in general intelligence or g. The Progressive Matrices (PM) Test is one of the best estimates of g. Males outperform females in the PM Test. Colom and Garcı´a-Lo´pez (2002) demonstrated that the information content has a role in the estimates of sex differences in general intelligence. The PM test is based on abstract figures and males outperform females in spatial tests. The present study administered the Advanced Progressive Matrices Test (APM) to a sample of 1970 applicants to a private University (1069 males and 901 females). It is predicted that there are several items biased against female performance, by virtue of their visuo-spatial nature. A double methodology is used. First, confirmatory factor analysis techniques are used to contrast one and two factor solutions. Second, Differential Item Functioning (DIF) methods are used to investigate sex DIF in the APM. The results show that although there are several biased items, the male advantage still remains. However, the assumptions of the DIF analysis could help to explain the observed results. [Copyright &y& Elsevier]

There is a renewed interest in the so-called differentiation theory. This theory states: the higher the level of g, the less the amount of g variance in any particular cognitive test. The implication of the differentiation theory for the scientific concept of intelligence is noteworthy: g could be more germane for low-ability than for high-ability people. A first battery of cognitive tests was applied to a sample of 3430 participants (mean age=23.12 years). The sample of the Spanish standardization of the WAIS-III was also analyzed (823 participants with a mean age=34.41 years). The methodology of Deary et al. [Intelligence 23 (1996) 105] was used for generating fine-grained low- and high-ability groups. The percentage of variance explained by g was computed for low- and high-ability groups, respectively: the mean percentages were 45.85 and 43.96 in the first cognitive battery, and 49.03 and 36.67 in the WAIS-III. These results support the differentiation of intelligence across the range of ability. However, a sample effect is observed: WAIS-III results are more supportive of the differentiation theory. This evidence suggests that ability differentiation could be related to educational differences. [Copyright &y& Elsevier]

Examines the scientific construct of general intelligence among tests scores. Summation on the standardized scores for IQ tests; Analysis of samples through Wechsler Adult Intelligence Scale-III; Correlation of human cognitive abilities with psychological science.

Abstract: Mackintosh and Bennett''s [Mackintosh, N. J. and Bennett, E. S, (2005). "What do Raven''s Matrices measure? An analysis in terms of sex differences." Intelligence 33: 663–674.] study shows that males outperform females in some APM items but not in others, implicating that these items are measuring discriminable mental processes. The present comment was motivated by the fact that the sample size considered by these authors was small, thus raising the possibility of a lack of reliability. To replicate their findings, data from the Abad et al.''s [Abad, F. J., Colom, R., Rebollo, I., & Escorial, S. (2004). Sex differential item functioning in the Raven''s Advanced Progressive Matrices: Evidence for bias. Personality and Individual Differences, 36(6): 1459–1470.] study were re-analyzed, but following the same criteria employed by Mackintosh and Bennett. The results are not consistent with those reported in their study, indicating that average sex differences remain fairly constant across the same groups of APM items considered by them. [Copyright &y& Elsevier]

There has been increased interest in assessing the quality and usefulness of short versions of the Raven's Progressive Matrices. A recent proposal, composed of the last twelve matrices of the Standard Progressive Matrices (SPM-LS), has been depicted as a valid measure of g. Nonetheless, the results provided in the initial validation questioned the assumption of essential unidimensionality for SPM-LS scores. We tested this hypothesis through two different statistical techniques. Firstly, we applied exploratory graph analysis to assess SPM-LS dimensionality. Secondly, exploratory bi-factor modelling was employed to understand the extent that potential specific factors represent significant sources of variance after a general factor has been considered. Results evidenced that if modelled appropriately, SPM-LS scores are essentially unidimensional, and that constitute a reliable measure of g. However, an additional specific factor was systematically identified for the last six items of the test. The implications of such findings for future work on the SPM-LS are discussed. [ABSTRACT FROM AUTHOR]

Cognitive diagnosis models (CDMs) are used in educational, clinical, or personnel selection settings to classify respondents with respect to discrete attributes, identifying strengths and needs, and thus allowing to provide tailored training/treatment. As in any assessment, an accurate reliability estimation is crucial for valid score interpretations. In this sense, most CDM reliability indices are based on the posterior probabilities of the estimated attribute profiles. These posteriors are traditionally computed using point estimates for the model parameters as approximations to their populational values. If the uncertainty around these parameters is unaccounted for, the posteriors may be overly peaked, deriving into overestimated reliabilities. This article presents a multiple imputation (MI) procedure to integrate out the model parameters in the estimation of the posterior distributions, thus correcting the reliability estimation. A simulation study was conducted to compare the MI procedure with the traditional reliability estimation. Five factors were manipulated: the attribute structure, the CDM model (DINA and G-DINA), test length, sample size, and item quality. Additionally, an illustration using the Examination for the Certificate of Proficiency in English data was analyzed. The effect of sample size was studied by sampling subsets of subjects from the complete data. In both studies, the traditional reliability estimation systematically provided overestimated reliabilities, whereas the MI procedure offered more accurate results. Accordingly, practitioners in small educational or clinical settings should be aware that the reliability estimation using model parameter point estimates may be positively biased. R codes for the MI procedure are made available [ABSTRACT FROM AUTHOR]

Gulliksen (1950) established the distinction between pure power and pure speed intelligence tests. Most standardized measures combine power and speed requirements. The speediness component affects test scores' reliability and validity, since it involves variance not due to the mental ability of interest. Here we propose the use of the Stafford's Speediness Quotient ( SQ , 1971) for identifying items biased by the speed component. We developed two converging methods based on Structural Equation Modeling (SEM) to assess the validity of the SQ index. The methods concurrently identify items substantially affected by speededness in three standardized fluid intelligence tests with different speed requirements. Basing on the SQ at the item level, a simple strategy for separating the power and speed components of mental ability tests applied under time constraints is proposed. This strategy allows an estimation of the respondents' level uncontaminated by the speed unwanted variance. This procedure only requires right/wrong responses (e.g., does not need any information external to the test, such as response times) and it is appropriate for medium-small sized samples. A rule of thumb is suggested for identifying items affected by speediness. The simplicity of the proposed procedure allows its use in applied settings for detecting and controlling speed-related variance in tests' scores. [ABSTRACT FROM AUTHOR]

Forced-choice questionnaires have been proposed as a way to control some response biases associated with traditional questionnaire formats (e.g., Likert-type scales). Whereas classical scoring methods have issues of ipsativity, item response theory (IRT) methods have been claimed to accurately account for the latent trait structure of these instruments. In this article, the authors propose the multi-unidimensional pairwise preference two-parameter logistic (MUPP-2PL) model, a variant within Stark, Chernyshenko, and Drasgow’s MUPP framework for items that are assumed to fit a dominance model. They also introduce a Markov Chain Monte Carlo (MCMC) procedure for estimating the model’s parameters. The authors present the results of a simulation study, which shows appropriate goodness of recovery in all studied conditions. A comparison of the newly proposed model with a Brown and Maydeu’s Thurstonian IRT model led us to the conclusion that both models are theoretically very similar and that the Bayesian estimation procedure of the MUPP-2PL may provide a slightly better recovery of the latent space correlations and a more reliable assessment of the latent trait estimation errors. An application of the model to a real data set shows convergence between the two estimation procedures. However, there is also evidence that the MCMC may be advantageous regarding the item parameters and the latent trait correlations. [ABSTRACT FROM AUTHOR]

As a general rule, the repeated administration of tests measuring a given cognitive ability in the same participants reveals increased scores. This brings to life the well-known practice effect and it must be taken into account in research aimed at the proper assessment of changes after the completion of cognitive training programs. Here we focus in one specific research question: Are changes in test scores accounted for by the tapped underlying cognitive construct/factor? The evaluation of the factor of interest by several measures is required for that purpose. 477 university students completed twice a battery of four heterogeneous standardized intelligence tests within a time lapse of four weeks. Between the pre-test and the post-test sessions, some participants completed eighteen practice sessions based on memory span tasks, other participants completed eighteen practice sessions based on processing speed tasks, and a third group of participants did nothing between testing sessions. The three groups showed remarkable changes in test scores from the pre-test to the post-test intelligence session. However, results from multi-group longitudinal latent variable analyses revealed that the identified latent factor tapped by the specific intelligence measures fails to account for the observed changes. [ABSTRACT FROM AUTHOR]

Abstract: Short-term adaptive cognitive training based on the n-back task is reported to increase scores on individual ability tests, but the key question of whether such increases generalize to the intelligence construct is not clear. Here we evaluate fluid/abstract intelligence (Gf), crystallized/verbal intelligence (Gc), working memory capacity (WMC), and attention control (ATT) using diverse measures, with equivalent versions, for estimating any changes at the construct level after training. Beginning with a sample of 169 participants, two groups of twenty-eight women each were selected and matched for their general cognitive ability scores and demographic variables. Under strict supervision in the laboratory, the training group completed an intensive adaptive training program based on the n-back task (visual, auditory, and dual versions) across twenty-four sessions distributed over twelve weeks. Results showed that this group had the expected systematic improvements in n-back performance over time; this performance systematically correlated across sessions with Gf, Gc, and WMC, but not with ATT. However, the main finding showed no significant changes in the assessed psychological constructs for the training group as compared with the control group. Nevertheless, post-hoc analyses suggested that specific tests and tasks tapping visuospatial processing might be sensitive to training. [Copyright &y& Elsevier]

Abstract: We investigated sex effects and the effects of educational attainment (EA) on the covariance structure of the WAIS-III in a subsample of the Spanish standardization data. We fitted both first order common factor models and second order common factor models. The latter include general intelligence (g) as a second order common factor. The results indicate that sex differences in means are due mainly to the WAIS-III factors Working Memory (WM) and Perceptual Organization (PO), rather than to the second order g factor. In treating EA as a predictor of the first common factors, we found that EA explained a significant, but clearly varying, amount of variance in the 4 first order common factors. Differences in explained variance over sex were very small. Treating EA as a predictor in the second order common factor model, we found that EA predicted g and first order factor Verbal Comprehension (VC). The relationships between PO, WM, and Perceptual Speed (PS) and EA are mediated by g. In treating EA as a dependent variable, we found that VC and PS were the only significant predictors of EA in the first order common factor model. In the second order common factor model, the same result was obtained. While VC and PS were significant predictors of EA, the second order factor g, and PO and WM were not. The results are of theoretical interest in the light of the Ankney–Rushton paradox, and the role of g in educational attainment. [Copyright &y& Elsevier]

There is great interest in the relationships between memory span tasks and cognitive abilities. However, the causes underlying their correlation remain unknown. In the present article, five key data sets were reanalyzed according to two criteria: They must consider complex span tasks (so-called working memory [WM] tasks) and simple span tasks (so-called short-term memory [STMI tasks), and they must comprise cognitive ability measures. The obtained results offer several points of interest. First, memory span tasks should be conceived from a hierarchical perspective: They comprise both general and specific components. Second, the general component explains about four times the variance explained by the specific components. Third, STM and WM measures are closely related. Fourth, STM and WM measures share the same common variance with cognitive abilities. Finally, the strong relationship usually found between memory span tasks and cognitive abilities could be tentatively interpreted by the component shared by STM and WM—namely, the capacity for temporarily preserving a reliable memory representation of any given information. [ABSTRACT FROM AUTHOR]

Generational intelligence test score gains have been documented worldwide in the twentieth century. However, recent evidence suggests these increased scores are coming to an end in some world regions. Here we compare two cohorts of university freshmen. The first cohort (n = 311) was assessed in 1991, whereas the second cohort (n = 349) was assessed thirty years later (2022). These cohorts completed the same intelligence battery including eight standardized speeded and power tests tapping reasoning (abstract and quantitative), language (vocabulary, verbal comprehension, and verbal meanings), rote calculation, and visuospatial relations. The results revealed a global gain of 3.5 IQ points but also upward and downward changes at the test level. The 2022 cohort outperformed the 1991 cohort on reasoning (abstract and quantitative), verbal comprehension, and vocabulary, whereas the 1991 cohort outscored the 2022 cohort on rote calculation, visuospatial relations (mental rotation and identical figures), and verbal meanings. These findings are thought to support one key claim made by James Flynn: generational changes on the specific cognitive abilities and skills tapped by standardized tests should be expected without appreciable or substantive changes in the structure of the intelligence construct identified within generations. This main conclusion is discussed with respect to theoretical causal implications putatively derived from current intelligence psychometric models. • Two cohorts of university freshmen separated by 30 years are compared. • A global gain equivalent to 3.5 IQ points is identified. • Upward and downward changes at the test level are identified. • These specific changes keep unaltered the structure of intelligence within generations. • The pattern of changes suggests theoretical implications for intelligence models. [ABSTRACT FROM AUTHOR]

Background: The development of an effective instrument to assess the risk of partner violence is a topic of great social relevance. This study evaluates the scale of "Predicción del Riesgo de Violencia Grave Contra la Pareja" --Revisada-- (EPV-R - Severe Intimate Partner Violence Risk Prediction Scale-Revised), a tool developed in Spain, which is facing the problem of how to treat the high rate of missing values, as is usual in this type of scale. Method: First, responses to the EPV-R in a sample of 1215 male abusers who were reported to the police were used to analyze the patterns of occurrence of missing values, as well as the factor structure. Second, we analyzed the performance of various imputation methods using simulated data that emulates the missing data mechanism found in the empirical database. Results: The imputation procedure originally proposed by the authors of the scale provides acceptable results, although the application of a method based on the Item Response Theory could provide greater accuracy and offers some additional advantages. Conclusions: Item Response Theory appears to be a useful tool for imputing missing data in this type of questionnaire. [ABSTRACT FROM AUTHOR]

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Background: Forced-choice tests (FCTs) were proposed to minimize response biases associated with Likert format items. It remains unclear whether scores based on traditional methods for scoring FCTs are appropriate for between-subjects comparisons. Recently, Hontangas et al. (2015) explored the extent to which traditional scoring of FCTs relates to the true scores and IRT estimates. The authors found certain conditions under which traditional scores (TS) can be used with FCTs when the underlying IRT model was an unfolding model. In this study, we examine to what extent the results are preserved when the underlying process becomes a dominance model. Method: The independent variables analyzed in a simulation study are: forced-choice format, number of blocks, discrimination of items, polarity of items, variability of intra-block difficulty, range of difficulty, and correlation between dimensions. Results: A similar pattern of results was observed for both models; however, correlations between TS and true thetas are higher and the differences between TS and IRT estimates are less discrepant when a dominance model involved. Conclusions: A dominance model produces a linear relationship between TS and true scores, and the subjects with extreme thetas are better measured. [ABSTRACT FROM AUTHOR]

This article explores how traditional scores obtained from different forced-choice (FC) formats relate to their true scores and item response theory (IRT) estimates. Three FC formats are considered from a block of items, and respondents are asked to (a) pick the item that describes them most (PICK), (b) choose the two items that describe them the most and the least (MOLE), or (c) rank all the items in the order of their descriptiveness of the respondents (RANK). The multi-unidimensional pairwise-preference (MUPP) model, which is extended to more than two items per block and different FC formats, is applied to obtain the responses to each item block. Traditional and IRT (i.e., expected a posteriori) scores are computed from each data set and compared. The aim is to clarify the conditions under which simpler traditional scoring procedures for FC formats may be used in place of the more appropriate IRT estimates for the purpose of inter-individual comparisons. Six independent variables are considered: response format, number of items per block, correlation between the dimensions, item discrimination level, and sign-heterogeneity and variability of item difficulty parameters. Results show that the RANK response format outperforms the other formats for both the IRT estimates and traditional scores, although it is only slightly better than the MOLE format. The highest correlations between true and traditional scores are found when the test has a large number of blocks, dimensions assessed are independent, items have high discrimination and highly dispersed location parameters, and the test contains blocks formed by positive and negative items. [ABSTRACT FROM AUTHOR]

The interactive relationship between educational level and IQ scores is still a matter of discussion, mainly because the latter combine the influence of (1) the general factor of intelligence ( g ), (2) cognitive abilities, and (3) cognitive skills. As underscored by Jensen (1998), among others, it is relevant to know how much of IQ scores is due to g and how much is due to specific abilities and skills. Separating the influence of these components may shed light regarding their relationship with educational level. Here we analyzed the standardization sample of the WAIS-R for Italy (N = 1630). We considered a) measurement invariance across four educational levels, and b) IQ variability and IQ differences due to g (general intelligence), VC (verbal comprehension), PO (perceptual organization), and MFD (Memory/Freedom from Distractibility). Results showed that (a) the WAIS-R provides a valid measure of latent g , (b) individual differences in intelligence are properly measured by IQ scores at different educational levels, (c) there is an average increase equal to 1.9 IQ points in the IQ global composite score per year of education, and (d) the relevance of g decreases at increased educational levels. [ABSTRACT FROM AUTHOR]

Abstract: Evidence from neuroimaging studies suggests that intelligence differences may be supported by a parieto-frontal network. Research shows that this network is also relevant for cognitive functions such as working memory and attention. However, previous studies have not explicitly analyzed the commonality of brain areas between a broad array of intelligence factors and cognitive functions tested in the same sample. Here fluid, crystallized, and spatial intelligence, along with working memory, executive updating, attention, and processing speed were each measured by three diverse tests or tasks. These twenty-one measures were completed by a group of one hundred and four healthy young adults. Three cortical measures (cortical gray matter volume, cortical surface area, and cortical thickness) were regressed against psychological latent scores obtained from a confirmatory factor analysis for removing test and task specific variance. For cortical gray matter volume and cortical surface area, the main overlapping clusters were observed in the middle frontal gyrus and involved fluid intelligence and working memory. Crystallized intelligence showed an overlapping cluster with fluid intelligence and working memory in the middle frontal gyrus. The inferior frontal gyrus showed overlap for crystallized intelligence, spatial intelligence, attention, and processing speed. The fusiform gyrus in temporal cortex showed overlap for spatial intelligence and attention. Parietal and occipital areas did not show any overlap across intelligence and cognitive factors. Taken together, these findings underscore that structural features of gray matter in the frontal lobes support those aspects of intelligence related to basic cognitive processes. [Copyright &y& Elsevier]

Examines the age differentiation in the number of cognitive abilities in Spain. Assessment on cognitive abilities by the Wechsler Adult Intelligence Scale-III; Relation of parameters to percentage of variance accounted; Analysis of factors through confirmatory factor analysis computed in every age group.

Industry 4.0 (I4.0) considers a number of changes in enterprises, including business models, to achieve the Smart Factory concept. This implies a complete communication network between different companies, factories, suppliers, resources, etc ..., maximize in real time to achieve the highest efficiency of all parties involved. The goal is to improve the performance and sustainability of shipbuilding industry through the supply chain establishing a model that defines how the supply chain should be under the perspective of Industry 4.0. Thus, this article aims to connect each of the key enabling I4.0 technologies with the most significant supply chain paradigms: Lean, Agile, Resilience and Green to define what the Shipbuilding Supply Chain should be. This study shows the Green Supply Chain Paradigm connects the social aspects required at the performance I4.0 model. Likewise, Lean represents the most important paradigm, encompassing the Resilience one, besides considering Agile as an intrinsic property of the shipbuilding. At this form, identifying the key factors in the conceptual model, it is possible to conclude that the Shipbuilding Supply Chain should be Green and Lean. • This article defines shipbuilding supply chain according to the performance model established in Industry 4.0. • Supply chain paradigms and the I4.0 technologies define a conceptual model of the shipbuilding supply chain. • The results obtained imply the implementation of technologies improving economic, energy profitability performance. • Second phase, satisfying functional and social requirements, achieve total visibility and connectivity required in 4.0. [ABSTRACT FROM AUTHOR]