Discriminating Between Attribute, Item-Position, and Wording Effects by the Congeneric and Tau-Equivalent Confirmatory Factor Analysis Models.

Ultra-short scales are increasingly popular in surveys. Congeneric model fit of a three-item scale cannot be tested with Confirmatory Factor Analysis (CFA) without additional assumptions because the number of degrees of freedom is equal to zero. A more rigorous tau-equivalent model, assuming equality of factor loadings can be tested instead. The objective of this study was to demonstrate this approach with an example of the psychometric study of the Polish version of the Three-Item Loneliness Scale (TILS), and to discuss the arising problems and possible solutions. There seems to be a high need for such analysis because currently, some properties of CFA make it an approach still predominant over Item Response Theory (IRT) models in the quality of life research. A sample of 3510 students completed TILS together with the questionnaires measuring a variety of indicators of well-being. The results provided evidence for a good fit of a tau-equivalent model. Furthermore, multi-group CFAs provided support for strict measurement invariance of this model. To the Authors’ knowledge, it is the first practical application of a tau-equivalent model to testing the factorial validity of an ultra-short scale and probably the first empirical case of tau-equivalent measurement invariance in psychological literature in general. TILS showed good criterion validity and satisfactory reliability. Unidimensionality of three-item scales can be examined with a tau-equivalent model that has some favorable psychometric properties. However, it might be exceedingly restrictive in certain practical cases. When developing a new short scale, it is recommended to maintain at least four items.

transfer, create conditions for the establishment of farmers' behavioral psychological contracts in the process of agricultural land transfers, and guide farmers to establish relationship psychological contracts. The second is to improve the market system, properly cultivate and develop agricultural land transfer intermediaries, reduce transaction costs, and reduce the probability of farmers' psychological contracts being broken. The third is to guide farmers to establish a positive agricultural land transfer psychology based on their resource endowments such as labor force quality and cultural quality, and encourage farmers to make agricultural land transfer decisions such as subcontracting, leasing, reselling, and interchanging.

BackgroundThe conceptualization of negative symptoms has been refined in the past decades. Two-factor model comprising Motivation and Pleasure (MAP) and Emotional Expressivity (EE), five-factor model representing five domains of negative symptoms and second-order five-factor model incorporating the two-factor and five-factor models (Anhedonia, Asociality and Avolition regressed on MAP; Blunted Affect and Alogia regressed on EE) have been suggested as latent structure of negative symptoms. In most studies, the item “Lack of Normal Distress” in the Brief Negative Symptom Scale (BNSS) did not fit well in factor models. Nevertheless, the reported correlation and item-total correlation of Distress with other negative symptom domains and BNSS items were not negligible. Emotion deficit was also discussed as a part of negative symptoms conceptualization. As a single item may not be sufficient to represent an underlying construct that is potentially abstract and complex, the Schedule for the Deficit Syndrome (SDS) which comprises “Diminished Emotional Range” that is conceptually relevant to the BNSS Distress was employed. The study aimed to reexamine the conceptualization of negative symptoms by examining the model fit of several models when BNSS Distress and SDS Emotion (EMO) were included in the models using confirmatory factor analyses (CFA).MethodsTwo-hundred and seventy-four schizophrenia outpatients aged 21–65 were assessed on the BNSS and SDS. In the two-factor models, Restricted Affect, Diminished Emotional Range and Poverty of Speech in SDS and all items in BNSS Blunted Affect and Alogia subscales were regressed on EE, Curbing of Interests, Diminished Sense of Purpose and Diminished Social Drive in SDS and all items in BNSS Anhedonia, Asociality and Avolition subscales were regressed on MAP, without EMO, or with EMO regressed on either EE or MAP. Five-factor models and second-order five-factor models were examined, with or without EMO. Lastly, a six-factor model with EMO manifested by the sixth factor and second-order six-factor models in which EMO was regressed on either EE or MAP were tested. Root mean square error of approximation (RMSEA) <0.08, comparative fit index (CFI) >0.95, the Tucker-Lewis Index (TLI) >0.95, and weighted root-mean-square residual (WRMR) <1.0 indicate good model fit. CFAs were conducted using Mplus version 7.4.ResultsThe two-factor models did not yield adequate fit indices. Five-factor model and second-order five-factor model without EMO had good model fit; five-factor model: RMSEA=0.056 (0.044–0.068), CFI=0.996, TFI=0.995, WRMR=0.718; second-order five-factor model: RMSEA=0.049 (0.036–0.061), CFI=0.997, TFI=0.996, WRMR=0.758. When EMO was included as indicator in one of the factors in the five-factor models, only the model in which EMO was regressed on Alogia yielded adequate fit. Similarly, in the second-order five-factor models, adequate fit indices were observed only when EMO was regressed on Alogia and Blunted Affect. The six-factor model fitted the data well, RMSEA=0.053 (0.042–0.064), CFI=0.996, TFI=0.995, WRMR=0.711. Second-order six-factor model with EMO regressed on EE yielded better model fit than MAP, RMSEA=0.050 (0.039–0.061), CFI=0.996, TFI=0.995, WRMR=0.849.DiscussionIn line with previous studies, five-factor and second-order five-factor models without EMO fitted the data well. When EMO was included, a six-factor model and a second-order six-factor model in which the sixth factor was regressed on EE showed good model fit. Emotion, motivation and behavior are intertwined. Our results showed that diminished emotion may also be one of the components of negative symptoms, which had higher association with EE than MAP.

Liste des Pensées Obsédantes (LPO) en version islandaise : étude des propriétés psychométriques avec une analyse factorielle confirmatoire

ABSTRACTThe current study has two main goals: (a) to identify a factor structure of the Daily Spiritual Experiences Scale (DSES) on a large archival data, collected from 1,325 adults in the United States (709 women, 616 men) by the U.S. General Social Survey in 2004 and (b) to examine the measurement invariance of the 16 DSES items between women and men in the same data to see whether any of the items are favoring or biased toward either women or men. The one-factor confirmatory factor analysis (CFA) model fit our data better than the two-factor CFA models because of high correlations between the two factors (r > .90). The fit of the one-factor CFA to our sample data was improved when we specified seven correlated residuals suggested by overlapping item content and large modification indices. The ensuing measurement invariance testing of the one-factor CFA model with seven correlated residuals supported full measurement invariance of factor loadings, thresholds, and residual variances, as well as factor variances between the women and the men. Yet the factor mean for the women was .841 units (Cohen’s d = .496) higher than it was for the men, indicating that higher levels of daily spiritual experiences for women reported in gender comparison studies in the United States are not likely to be an artifact of bias in the questionnaire.

Conceptualizing two-variable disturbances preventing good model fit in confirmatory factor analysis as item-level method effects instead of correlated residuals avoids violating the principle that residual variation is unique for each item. The possibility of representing such a disturbance by a method factor of a bifactor measurement model was investigated with respect to model identification. It turned out that a suitable way of realizing the method factor is its integration into a fixed-links, parallel-measurement or tau-equivalent measurement submodel that is part of the bifactor model. A simulation study comparing these submodels revealed similar degrees of efficiency in controlling the influence of two-variable disturbances on model fit. Perfect correspondence characterized the fit results of the model assuming correlated residuals and the fixed-links model, and virtually also the tau-equivalent model.

Evaluation and comparison of the factor structure of the Medical Outcomes Study Social Support Survey (MOS-SSS) using both confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) with two samples of people living with HIV/AIDS in China. Secondary analyses were conducted with data from two comparable samples of 320 people living with HIV/AIDS from the same hospital using the same inclusion criteria. The first sample of 120 was collected in 2006, and the second sample of 200 was collected in 2012. For each sample, CFA was first performed on the original four-factor structure to check model fit, followed by EFA to explore other factor structures and a subsequent CFA for model fit statistics to be compared to the original four-factor CFA. In both samples, CFA on the originally hypothesized four-factor structure yielded an acceptable model fit. The EFA yielded a two-factor solution in both samples, with different items included in each factor for the two samples. Comparison of CFA on the a priori four-factor structure and the new two-factor structure in both samples indicated that both factor structures were of acceptable model fit, with the four-factor model performing slightly better than the two-factor model. Factor structure of the MOS-SSS is method-dependent, with CFA supporting a four-factor structure, while EFA yielded a two-factor structure in two separate samples. We need to be careful in selecting the analytic method when applying the MOS-SSS to various samples and choose the factor structure that best fits the theoretical model.

The current article compares the use of exploratory structural equation modeling (ESEM) as an alternative to confirmatory factor analytic (CFA) models in personality research. We compare model fit, factor distinctiveness, and criterion associations of factors derived from ESEM and CFA models. In Sample 1 (n = 336) participants completed the NEO-FFI, the Trait Emotional Intelligence Questionnaire-Short Form, and the Creative Domains Questionnaire. In Sample 2 (n = 425) participants completed the Big Five Inventory and the depression and anxiety scales of the General Health Questionnaire. ESEM models provided better fit than CFA models, but ESEM solutions did not uniformly meet cutoff criteria for model fit. Factor scores derived from ESEM and CFA models correlated highly (.91 to .99), suggesting the additional factor loadings within the ESEM model add little in defining latent factor content. Lastly, criterion associations of each personality factor in CFA and ESEM models were near identical in both inventories. We provide an example of how ESEM and CFA might be used together in improving personality assessment.

Estimation of composite reliability within a hierarchical modeling framework has recently become of particular interest given the growing recognition that the underlying assumptions of coefficient alpha are often untenable. Unfortunately, coefficient alpha remains the prominent estimate of reliability when estimating total scores from a scale with a hierarchical structure, in part because there are few published articles that provide a step-by-step demonstration of how to estimate reliability within the context of structural equation modeling. Using AMOS 22 to analyze simulated and Wechsler Adult Intelligence Scale–Fourth Edition (WAIS-IV) summary data, the authors demonstrate how to compare the fit and reliability estimates of a (a) second-order confirmatory factor analytic (CFA) model, (b) bifactor model, and (c) essentially tau-equivalent model, which conforms to the stringent assumptions underlying coefficient alpha. The variance–covariance matrices generated from the simulated data as well as the WAIS-IV data are provided to allow for replication of results.

To evaluate the underlying factor structure of the Chinese version of General Health Questionnaire-12 using exploratory and confirmatory factor analyses in Chinese adolescents and find out which factor model proposed by previous empirical research is the best-fit model. The 12-item General Health Questionnaire has been extensively used with adolescents in the West. Yet, it has not been used with adolescents in a Hong Kong Chinese context. A cross-sectional study was employed. Chinese students between the ages of 12-19 from four secondary schools were invited to participate in the study using the multiple-stage stratified random sampling method during the period from December 2007-February, 2008. The total sample size included in the final analysed was 1883. The General Health Questionnaire-12 was found to be internally consistent. The results of exploratory factor analysis showed that there are two factors underlying the General Health Questionnaire-12. Of nine factor models were tested by means of confirmatory factor analysis, only three factor model: the eight-item two-factor model, 12-item three-factor model and 10-item two-factor model, demonstrated good model fit across all model fit indices. This study addressed a gap in the literature by evaluating the factorial structure of the Chinese version of General Health Questionnaire-12 using exploratory and confirmatory factor analyses in Chinese adolescents. The findings revealed that the eight-item two-factor model is the best-fit model. The adolescent mental health problem is alarming and aggravating and warrants special attention. It is essential for community nurses to differentiate psychological distress in adolescents and to identify those adolescents who are at a higher risk of suffering from mental health problems. The availability of a valid and reliable instrument that measures adolescents' psychological distress is crucial before any nursing interventions to promote their mental health can be appropriately planned, implemented and evaluated.

Vaccine hesitancy amongst healthcare workers (HCWs) has been a major challenge throughout the COVID-19 pandemic. While many studies have identified HCW characteristics and specific attitudes associated with COVID-19 vaccine hesitancy, researchers are still working towards developing a holistic understanding of the psychological constructs that influence COVID-19 vaccine decision-making in this population. Between 15 March and 29 March 2021, we distributed an online survey assessing individual characteristics and vaccine-related perceptions to employees of a not-for-profit healthcare system in Southwest Virginia (N = 2459). We then performed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to describe patterns of vaccine-related thought amongst HCWs and identify latent psychometric constructs involved in vaccine decision-making. The goodness of model fit was assessed using the Tucker-Lewis Index (TLI), the Comparative Fit Index (CFI), and the Root Mean Square Error of Approximation (RMSEA). Internal consistency and reliability of each factor were assessed using Cronbach's alpha. EFA identified four latent psychometric constructs: Lack of trust in the COVID-19 vaccine; Anti-science sentiment; Adverse side-effects; and Situational risk assessment. The goodness of EFA model fit was adequate (TLI > 0.90, RMSEA ≤ 0.08) with acceptable internal consistency and reliability for three of four factors (Cronbach's alpha > 0.70). The CFA model also had adequate goodness of fit (CFI > 0.90, RMSEA ≤ 0.08). We believe the psychometric constructs identified in this study can provide a useful framework for interventions to improve vaccine uptake amongst this critical population.

Objective The Dental Activities Test (DAT) was developed to be used by dental, nursing, and other health professionals to assess the ability of persons with dementia to perform oral health-related activities and aid care planning. The instrument was designed as a unitary scale and has excellent internal consistency, test-retest reliability, interrater reliability, and construct validity. This study examines the underlying factor structure of the DAT among older adults in assisted living settings. Methods In a secondary analysis of the data from the original study, the results of testing of 90 older adults with normal to severely impaired cognition from three assisted living communities in North Carolina from March 2013 to February 2014 were studied. An exploratory factor analysis was used to assess the dimensionality of the presumed unitary assessment scale. Results Two-factor structures were explored. A one-factor model demonstrated acceptably mixed model fit, and a two-factor model had good model fit with moderate correlation between the two factors (r = 0.667, p < 0.05). All the items in the one-factor model demonstrated significant factor loadings (loadings ≥ 0.39, all p < 0.05), while the loadings of some items in the two-factor model (nonsignificant or cross-loadings, loadings < 0.40) did not meet the criteria of factor selection. The one-factor structure was preferred based on the criteria of Scree Plot, eigenvalue, and factor interpretability in relation to clinical relevance. Conclusions The study provided preliminary evidence that the Dental Activities Test has a unidimensional construct among older adults with cognitive impairment. It suggested that this instrument can be used as a unitary scale to assess dental-related function in persons with dementia. Future testing, including using a confirmatory factor analysis, in a new sample is needed to further assess the usefulness and psychometric properties of this instrument.

Background. Phlegm pattern questionnaire (PPQ) was developed to evaluate and diagnose phlegm pattern in Korean Medicine and Traditional Chinese Medicine, but it was based on a dataset from patients who visited the hospital to consult with a clinician regarding their health without any strict exclusion or inclusion. In this study, we reinvestigated the construct validity of PPQ with a new dataset and confirmed the feasibility of applying it to a healthy population. Methods. 286 healthy subjects were finally included and their responses to PPQ were acquired. Confirmatory factor analysis (CFA) was conducted and the model fit was discussed. We extracted a new factor structure by exploratory factor analysis (EFA) and compared the two factor structures. Results. In CFA results, the model fit indices are acceptable (RMSEA = 0.074) or slightly less than the good fit values (CFI = 0.839, TLI = 0.860). Many average variances extracted were smaller than the correlation coefficients of the factors, which shows the somewhat insufficient discriminant validity. Conclusions. Through the results from CFA and EFA, this study shows clinically acceptable model fits and suggests the feasibility of applying PPQ to a healthy population with relatively good construct validity and internal consistency.

This study employs confirmatory factor analysis techniques to reanalyse the correlation matrix computed from the data gathered by Ainley (1985). The data consisted of 227 teacher education students from different tertiary colleges. Ainley used five (12 subscales) frequently used questionnaire measures of curiosity in her study. The purpose of the present study was to test the statistical fit of the two-factor model of curiosity subsuming two styles—breadth of interest and depth of interest. Application of goodness-of-fit indexes offered by the LISREL program revealed that the two-factor orthogonal model fitted the data poorly. Using confirmatory factor analysis in an exploratory fashion a tentative three-factor confirmatory factor model was constructed. The third factor can be labelled as “venturesomeness” or “physical thrill-seeking”. The fit of the three-factor model was significantly better statistically than the two-factor model. With the help of a specification search it was still possible t...

The Disease Activity index for Psoriatic Arthritis (DAPSA) was developed to assess disease activity in patients with psoriatic arthritis (PsA). A modified version, DAPSA28, uses 28 joints instead of 66/68. This study evaluated key psychometric properties of DAPSA and DAPSA28. Data from 1865 patients with PsA in the European Spondyloarthritis (EuroSpA) Research Collaboration Network, having DAPSA and DAPSA28 scores at baseline and follow-up, were analysed. Tests included assessment of internal construct validity by scree plots, confirmatory factor analysis (CFA) and structural equation modelling (SEM), supplemented by tests of differential item functioning (DIF) and evaluation of internal consistency reliability by Cronbach's α (CA). A subset of 625 patients was used for most analyses, except descriptive statistics, correlation matrix and CA. One-dimensional CFA models for DAPSA and DAPSA28 showed acceptable model fit at baseline (root mean square error of approximation, RMSEA: 0.020, 0.034). However, model fit at 6 months follow-up was poor (RMSEA: 0.057, 0.063). SEM combining baseline and follow-up data could not identify an acceptable model fit. DIF was found for sex and country. CA indicated acceptable internal consistency (DAPSA: 0.65; DAPSA28: 0.63). Heterogeneity across countries was observed. Overall, the model fit was acceptable across model fit statistics, supporting internal construct validity, but some evidence of misfit at country level was disclosed. Our findings support acceptable internal consistency reliability, but DIF was found for sex and country. Based on mixed results of model fit and DIF, further investigation of these and other PsA disease activity measures is warranted.