Examining the factor structure and its replicability across multiple listening test forms: Validity evidence for the Michigan English Test

This study evaluated the validity of the Michigan English Test (MET) Listening Section by investigating its underlying factor structure and the replicability of its factor structure across multiple test forms. Data from 3255 test takers across four forms of the MET Listening Section were used. To investigate the factor structure, each form was fitted with four Bayesian confirmatory factor analysis (CFA) models: (1) a three correlated-factor model, (2) a bi-factor model, (3) a higher-order factor model, and (4) a single general-factor model. In addition, a four-pronged heuristic comprising construct delineation, construct operationalization, factor structure analysis, and congruence coefficient was developed to examine the replicability of factor structures across the test forms. Results from the CFA models showed that the test forms were unidimensional and the four-pronged heuristic indicated that the test construct was consistently operationalized across forms. Furthermore, the congruence coefficient indicated that the factor structure representing listening was highly similar and replicable across test forms. In sum, the construct of the MET Listening Section did not comprise divisible subskills. Yet, the unidimensional factor structure of the test was replicable across the test forms.

Data-Driven Dietary Patterns and Diet Quality Scores: Reproducibility and Consistency in Sex and Age Subgroups of Poles Aged 15–65 Years

This study aimed to assess: (i) the test–retest reproducibility of identification of data-driven dietary patterns (DPs) derived using a Principal Component Analysis (PCA) and hypothesis-driven DPs (diet quality scores); (ii) the consistency of data-driven DPs with diet quality scores in sex and age subgroups of Poles aged 15–65 years. The study involved 504 subjects (55.6% of females). Data on food consumption frequency (33 food items) were collected twice with a two-week interval using the Dietary Habits and Nutrition Beliefs Questionnaire (KomPAN®) in a self-administered version (test and retest). Two major data-driven DPs (‘Prudent’ and ‘Western’) were identified in the total sample, sex groups and four age groups separately from test and retest data. Two diet quality scores were analysed: Pro-Healthy-Diet-Index-10 (pHDI-10) and Non-Healthy-Diet-Index-14 (nHDI-14). Tucker’s congruence coefficient indicated fair-to-good similarity of data-driven DPs between test and retest for all study subgroups, except for males. Across study subgroups, the intraclass correlation coefficient (ICC) between the test and retest ranged from 0.56 to 0.86 for ‘Prudent’ DP and 0.57 to 0.82 for ‘Western’ DP, with the lowest values in males. The ICC (test vs. retest) ranged from 0.84 to 0.88 for pHDI-10 and 0.75 to 0.88 for nHDI-14. Comparing the data-driven DPs and diet quality scores, the Spearman’s correlations ranged from 0.63 to 0.93 between ‘Prudent’ DP and pHDI-10, and from 0.60 to 0.81 between ‘Western’ DP and nHDI-14. The test–retest reproducibility of data-driven DPs and diet quality scores and their consistency were acceptable in most of the study subgroups, with a tendency to be higher for pro-health than unhealthy DPs. Data-driven DPs were more reproducible in females than males. The reproducibility of diet quality scores tended to be better in males than females and was the highest in 25–44-year-olds. The KomPAN® questionnaire can be recommended to use data-driven DPs and diet quality scores to describe the habitual diet in people aged 15–65 years.

Fold recognition by scoring protein maps using the congruence coefficient

Motivation Protein fold recognition is a key step for template-based modeling approaches to protein structure prediction. Although closely related folds can be easily identified by sequence homology search in sequence databases, fold recognition is notoriously more difficult when it involves the identification of distantly related homologs. Recent progress in residue–residue contact and distance prediction opens up the possibility of improving fold recognition by using structural information contained in predicted distance and contact maps. Results Here we propose to use the congruence coefficient as a metric of similarity between maps. We prove that this metric has several interesting mathematical properties which allow one to compute in polynomial time its exact mean and variance over all possible (exponentially many) alignments between two symmetric matrices, and assess the statistical significance of similarity between aligned maps. We perform fold recognition tests by recovering predicted target contact/distance maps from the two most recent Critical Assessment of Structure Prediction editions and over 27 000 non-homologous structural templates from the ECOD database. On this large benchmark, we compare fold recognition performances of different alignment tools with their own similarity scores against those obtained using the congruence coefficient. We show that the congruence coefficient overall improves fold recognition over other methods, proving its effectiveness as a general similarity metric for protein map comparison. Availability and implementation The congruence coefficient software CCpro is available as part of the SCRATCH suite at: http://scratch.proteomics.ics.uci.edu/. Supplementary information Supplementary data are available at Bioinformatics online.

Fold recognition by scoring protein map similarities using the congruence coefficient

MotivationProtein fold recognition is a key step for template-based modeling approaches to protein structure prediction. Although closely related folds can be easily identified by sequence homology search in sequence databases, fold recognition is notoriously more difficult when it involves the identification of distantly related homologues. Recent progress in residue-residue contact and distance prediction opens up the possibility of improving fold recognition by using structural information contained in predicted distance and contact maps.ResultsHere we propose to use the congruence coefficient as a metric of similarity between maps. We prove that this metric has several interesting mathematical properties which allow one to compute in polynomial time its exact mean and variance over all possible (exponentially many) alignments between two symmetric matrices, and assess the statistical significance of similarity between aligned maps. We perform fold recognition tests by recovering predicted target contact/distance maps from the two most recent CASP editions and over 27,000 non-homologous structural templates from the ECOD database. On this large benchmark, we compare fold recognition performances of different alignment tools with their own similarity scores against those obtained using the congruence coefficient. We show that the congruence coefficient overall improves fold recognition over other methods, proving its effectiveness as a general similarity metric for protein map comparison.AvailabilityThe software CCpro is available as part of the Scratch suite http://scratch.proteomics.ics.uci.edu/

A modified tucker’s congruence coefficient for factor matching

Since factor analysis is one of the most often used techniques in psychometrics, comparing or combining solutions from different factor analyses is often needed. Several measures to compare factors exist, one of the best known is Tucker’s congruence coefficient, which is enjoying newly found popularity thanks to the recent work of Lorenzo-Seva and ten Berge (2006), who established cut-off values for factor congruence. While this coefficient is in most cases very good in comparing factors in general, it also has some disadvantages, which can cause trouble when one needs to compare or combine many analyses. In this paper, we propose a modified Tucker’s congruence coefficient to address these issues.

Multicultural Validation of the Zuckerman–Kuhlman–Aluja Personality Questionnaire Shortened Form (ZKA-PQ/SF) Across 18 Countries

The aim of this study was to assess the psychometric properties of the Zuckerman–Kuhlman–Aluja Personality Questionnaire shortened form (ZKA-PQ/SF) in 18 cultures and 13 languages of different African, American, Asian, and European cultures and languages. The results showed that the five-factor structure with 20 facets replicated well across cultures with a total congruence coefficient of .97. A confirmatory factor analysis (CFA) resulted in adequate fit indices for the five factors based on the comparative fit index (CFI), Tucker–Lewis index (TLI; >.90), and RMSEA (.031-.081). A series of CFA to assess measurement invariance across cultures resulted in adequate CFIs and TLIs for configural and metric invariance. However, factors did not show scalar invariance. Alpha internal consistencies of five factors ranged between .77 (Sensation Seeking) and .86 (Neuroticism). The average alpha of the 20 facets was .64 with a range from .43 (SS4) to .75 (AG1). Nevertheless, alpha reliabilities were lower in some facets and cultures, especially for Senegal and Togo. The average percentage of the variance explained based on the adjusted R2 was 2.9%, 1.7%, and 5.1% for age, sex, and, cultures, respectively. Finally, multidimensional scaling suggested that geographically or culturally close cultures share mean profile similarities.

Joint factorial structure of psychopathology and personality

BackgroundNormative and pathological personality traits have rarely been integrated into a joint large-scale structural analysis with psychiatric disorders, although a recent study suggested they entail a common individual differences continuum.MethodsWe explored the joint factor structure of 11 psychiatric disorders, five personality-disorder trait domains (DSM-5 Section III), and five normative personality trait domains (the ‘Big Five’) in a population-based sample of 2796 Norwegian twins, aged 19‒46.ResultsThree factors could be interpreted: (i) a general risk factor for all psychopathology, (ii) a risk factor specific to internalizing disorders and traits, and (iii) a risk factor specific to externalizing disorders and traits. Heritability estimates for the three risk factor scores were 48% (95% CI 41‒54%), 35% (CI 28‒42%), and 37% (CI 31‒44%), respectively. All 11 disorders had uniform loadings on the general factor (congruence coefficient of 0.991 with uniformity). Ignoring sign and excluding the openness trait, this uniformity of factor loadings held for all the personality trait domains and all disorders (congruence 0.983).ConclusionsBased on our findings, future research should investigate joint etiologic and transdiagnostic models for normative and pathological personality and other psychopathology.

Micro Thin-Layer Chromatography Fingerprints of Selected Basil Species and Their Chemometric Analysis

The dried aerial parts of 12 plants of Ocimum spp. were extracted with the Soxhlet apparatus using dichloromethane and methanol as solvents. A micro-TLC system with silica and a normal-phase solvent system (propan-2-ol–n-heptane–formic acid) was used for the chemometric analysis of 12 selected basil methanolic extracts. Some indices of similarity (Pearson's correlation coefficient, determination coefficient, congruence coefficient, and Euclidean, Manhattan (city-block), Chebyshev, and Hausdorff distances) were calculated on the basis of thin-layer chromatograms using ImageJ software. Principal component analysis was also performed. The method allowed the comparison of the analyzed extracts and confirmed the identities of two selected unknown plants.