Common Factor Structure Research Articles

Common Factor Structure of the Ten Subtest Wechsler Adult Intelligence Scale-Fourth Edition in a Clinical Sample and 15 Subtest Version in the Standardization Sample.

The 10 core subtests of the Wechsler Adult Intelligence Scale-IV (WAIS-IV) suffice to produce the 4 index scores for clinical assessments. Factor analytic studies with the full complement of 15 subtests reveal a 5-factor structure that aligns with Cattell-Horn-Carroll taxonomy of cognitive abilities. The current study investigates the validity of 5-factor structure in a clinical setting with reduced number of 10 subtests. Confirmatory factor analytic models were fitted to a clinical neurosciences archival data set (n_Male = 166, n_Female = 155) and to 9 age-group samples of the WAIS-IV standardization data (n = 200 for each group). The clinical and the standardization samples differed as (a) the former comprised scores from patients, aged 16 to 91, with disparate neurological diagnosis whereas the latter was demographically stratified, (b) only the 10 core subtests in the former but all 15 subtests in the latter were administered, and (c) the former had missing data, but the latter was complete. Despite empirical constraints to eliciting 5 factors with only 10 indicators, the well-fitting, 5-factor (acquired knowledge, fluid intelligence, short-term memory, visual processing, and processing speed) measurement model evinced metric invariance between the clinical and standardization samples. The same cognitive constructs are measured on the same metrics in every sample examined and provide no reason to reject the assumption that the 5 underlying latent abilities of the 15 subtest version in the standardization samples can also be inferred from the 10 subtest version in clinical populations.

The shared genetic architecture of suicidal behaviour and psychiatric disorders: A genomic structural equation modelling study.

Background: Suicidal behaviour (SB) refers to behaviours, ranging from non-fatal suicidal behaviour, such as suicidal ideation and attempt, to completed suicide. Despite recent advancements in genomic technology and statistical methods, it is unclear to what extent the spectrum of suicidal behaviour is explained by shared genetic aetiology. Methods: We identified nine genome-wide association statistics of suicidal behaviour (sample sizes, n, ranging from 62,648 to 125,844), ten psychiatric traits [n up to 386,533] and collectively, nine summary datasets of anthropometric, behavioural and socioeconomic-related traits [n ranging from 58,610 to 941,280]. We calculated the genetic correlation among these traits and modelled this using genomic structural equation modelling, identified shared biological processes and pathways between suicidal behaviour and psychiatric disorders and evaluated potential causal associations using Mendelian randomisation. Results: Among populations of European ancestry, we observed strong positive genetic correlations between suicide ideation, attempt and self-harm (rg range, 0.71-1.09) and moderate to strong genetic correlations between suicidal behaviour traits and a range of psychiatric disorders, most notably, major depression disorder (rg = 0.86, p = 1.62 × 10-36). Multivariate analysis revealed a common factor structure for suicidal behaviour traits, major depression, attention deficit hyperactivity disorder (ADHD) and alcohol use disorder. The derived common factor explained 38.7% of the shared variance across the traits. We identified 2,951 genes and 98 sub-network hub genes associated with the common factor, including pathways associated with developmental biology, signal transduction and RNA degradation. We found suggestive evidence for the protective effects of higher household income level on suicide attempt [OR = 0.55 (0.44-0.70), p = 1.29 × 10-5] and while further investigation is needed, a nominal significant effect of smoking on suicide attempt [OR = 1.24 (1.04-1.44), p = 0.026]. Conclusion: Our findings provide evidence of shared aetiology between suicidal behaviour and psychiatric disorders and indicate potential common molecular mechanisms contributing to the overlapping pathophysiology. These findings provide a better understanding of the complex genetic architecture of suicidal behaviour and have implications for the prevention and treatment of suicidal behaviour.

The permanent or transitory nature of shocks to tourism expenditures and receipts: Evidence from new panel stationarity tests with breaks and factors

Tourism expenditures and receipts are an important component of many countries’ balance of payments. Indeed, the determination of whether shocks to tourism expenditures and receipts are permanent or transitory in nature is relevant to understanding the appropriate policy response. This study introduces new panel stationarity tests that simultaneously model structural breaks and a common factor structure. The results from several panel stationarity tests including the new tests reject the null hypothesis of stationarity for the panel of 63 countries. Based on tests of stationarity with a common factor structure without structural breaks at the individual country level, the null hypothesis of stationarity is rejected in 24 and 26 countries with respect to per capita international tourism expenditures and tourism receipts, respectively. The inclusion of the Fourier approximation for smooth structural breaks alongside the common factor structure increases the number of rejections of the null hypothesis of stationarity to 48 and 54 countries for per capita international tourism expenditures and receipts, respectively. Hence, shocks to either tourism expenditures or receipts will likely be permanent in nature requiring a policy response in order to return tourism expenditures and receipts to their original trend path. JEL Codes: Z32, C33.

Robust Estimation of Large Panels with Factor Structures

This article studies estimation of linear panel regression models with heterogeneous coefficients using a class of weighted least squares estimators, when both the regressors and the error possibly contain a common latent factor structure. Our theory is robust to the specification of such a factor structure because it does not require any information on the number of factors or estimation of the factor structure itself. Moreover, our theory is efficient, in certain circumstances, because it nests the GLS principle. We first show how our unfeasible weighted-estimator provides a bias-adjusted estimator with the conventional limiting distribution, for situations in which the OLS is affected by a first-order bias. The technical challenge resolved in the article consists of showing how these properties are preserved for the feasible weighted estimator in a double-asymptotics setting. Our theory is illustrated by extensive Monte Carlo experiments and an empirical application that investigates the link between capital accumulation and economic growth in an international setting. Supplementary materials for this article are available online.

Satın Alma Gücü Paritesi Geçerliliğinin Fourier Birim Kök Testi ile İncelenmesi: N-11 Ülkeleri Örneği

Purchasing power parity (PPP) is an approach which is based on the law of one price and balances the purchasing power of currencies by excluding price differences among countries. The interest in the PPP hypothesis, which is also used as an international development criteria, has been increasing due to price instability and trade deficits faced by countries. Along with the increasing interest, the validity of the PPP hypothesis is tested more often for different country groups and time periods by using modern analysis methods. The aim of this study is to test the validity of the PPP hypothesis for the period 1970-2019 in nine of N-11 countries. Accordingly, the BCIPS unit root analysis method, which allows for cross-section dependence, soft breaks, and common factor structure and which was proposed by Lee, Wu, and Yang (2016), was used as a modern test technique in the study. The findings of the analysis suggest that the real exchange rates for N-11 countries are stationary, therefore, it is concluded that the PPP hypothesis is valid. In this respect, it is revealed that the effect of shocks on the real (effective) exchange rate in N-11 countries is temporary and that PPP can be used as a reliable indicator in monetary policy decisions and international development measures.

PERTURBED FACTOR ANALYSIS: ACCOUNTING FOR GROUP DIFFERENCES IN EXPOSURE PROFILES.

In this article we investigate group differences in phthalate exposure profiles using NHANES data. Phthalates are a family of industrial chemicals used in plastics and as solvents. There is increasing evidence of adverse health effects of exposure to phthalates on reproduction and neurodevelopment and concern about racial disparities in exposure. We would like to identify a single set of low-dimensional factors summarizing exposure to different chemicals, while allowing differences across groups. Improving on current multigroup additive factor models, we propose a class of Perturbed Factor Analysis (PFA) models that assume a common factor structure after perturbing the data via multiplication by a group-specific matrix. Bayesian inference algorithms are defined using a matrix normal hierarchical model for the perturbation matrices. The resulting model is just as flexible as current approaches in allowing arbitrarily large differences across groups but has substantial advantages that we illustrate in simulation studies. Applying PFA to NHANES data, we learn common factors summarizing exposures to phthalates, while showing clear differences across groups.

Large-scale evaluation of the Positive and Negative Syndrome Scale (PANSS) symptom architecture in schizophrenia.

Although the Positive and Negative Syndrome Scale (PANSS) is widely utilized in schizophrenia research, variability in specific item loading exist, hindering reproducibility and generalizability of findings across schizophrenia samples. We aim to establish a common PANSS factor structure from a large multi-ethnic sample and validate it against a meta-analysis of existing PANSS models. Schizophrenia participants (N = 3511) included in the current study were part of the Singapore Translational and Clinical Research Program (STCRP) and the Clinical Antipsychotic Trials for Intervention Effectiveness (CATIE). Exploratory Factor Analysis (EFA) was conducted to identify the factor structure of PANSS and validated with a meta-analysis (N = 16,171) of existing PANSS models. Temporal stability of the PANSS model and generalizability to individuals at ultra-high risk (UHR) of psychosis were evaluated. A five-factor solution best fit the PANSS data. These were the i) Positive, ii) Negative, iii) Cognitive/disorganization, iv) Depression/anxiety and v) Hostility factors. Convergence of PANSS symptom architecture between EFA model and meta-analysis was observed. Modest longitudinal reliability was observed. The schizophrenia derived PANSS factor model fit the UHR population, but not vice versa. We found that two other domains, Social Amotivation (SA) and Diminished Expression (DE), were nested within the negative symptoms factor. Here, we report one of the largest transethnic factorial structures of PANSS symptom domains (N = 19,682). Evidence reported here serves as crucial consolidation of a common PANSS structure that could aid in furthering our understanding of schizophrenia.

Validation of the Polish version of the Unified Dyskinesia Rating Scale (UDysRS).

In 2008, the Movement Disorders Society published the Unified Dyskinesia Rating Scale (UDysRS). This has become the established tool for assessing the severity and disability associated with dyskinesia in patients with Parkinson's Disease (PD). We translated and validated the Polish version of the UDysRS, explored its dimensionality, and compared it to the Spanish version, which is the Reference Standard for UDysRS translations. The UDysRS was translated into Polish by a team led by JS and GO. The back-translation, completed by colleagues fluent in both Polish and English who were not involved in the original translation, was reviewed and approved by the Executive Committee of the MDS Rating Scales Programme. Then the translated version of the UDysRS underwent cognitive pretesting, and the translation was modified based on the results. The approved version was considered to be the Official Working Document of the Polish UDysRS and was tested on 250 Polish PD patients recruited at movement disorder centres. Data was compared to the Reference Standard used for validating UDysRS translations. The overall factor structure of the Polish version was consistent with that of the Reference Standard version, as evidenced by the high Confirmatory Fit Index score (CFI = 0.98). The Polish UDysRS was thus confirmed to share a common factor structure with the Reference Standard. The Official Polish UDysRS translation is recommended for use in clinical and research settings. Worldwide use of uniform rating measures offers a common ground to study similarities and differences in disease manifestations and progression across cultures.

How Common are Return Factors in Cryptocurrencies and Equities?

Finance research contributes to finding factors to explain the cross-sectional expected equity and cryptocurrency returns. In this paper, we implement the statistical methods to evaluate the common factor structure of these two markets and aim to identify the possible common factors across two markets. By considering the comprehensive dataset covering cryptocurrencies and the U.S. equity universe, we find that there are no common pervasive factors that govern the returns for both cryptocurrencies and equities before 2019, but there arises one common factor post-2020. The identified common factor is significantly related to the standard equity factors but not the crypto factors, which suggests that equity factors can help explain the common variations in returns across equities and cryptocurrencies. The documented pattern is robust across different U.S. equity market classifications, return specifications, and implemented statistical methods. Moreover, we find this pattern holds at the international equity market level. Our results point to the arising of common factors driving the returns on these two markets. Specifically, it's the equity factors that contribute to explaining the cross-sectional cryptocurrency returns recently.

Multifactor Models and Their Consistency with the APT

Abstract We examine the consistency of several prominent multifactor models from the empirical asset pricing literature with the arbitrage pricing theory (APT) framework. We follow the APT-related literature and estimate the common factor structure from a rich cross-section (associated with 42 major CAPM anomalies) by employing the asymptotic principal components method. Our benchmark model contains six statistical factors and clearly dominates, in both economic and statistical terms, most of the empirical multifactor models proposed in the literature by a good margin. These results represent a critical challenge to the current workhorse models in terms of explaining large-scale equity risk premiums. (JEL G10, G12) Received December 27, 2019; editorial decision October 20, 2020 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Testing capital asset pricing models using functional-coefficient panel data models with cross-sectional dependence

This paper proposes a functional-coefficient panel data model with cross-sectional dependence motivated by re-examining the empirical performance of conditional capital asset pricing model. In order to characterize the time-varying property of assets’ betas and alpha, our proposed model allows the betas to be unknown functions of some macroeconomic and financial instruments. Moreover, a common factor structure is introduced to characterize cross-sectional dependence which is an attractive feature under a panel data regression setting as different assets or portfolios may be affected by same unobserved shocks. Compared to the existing studies, such as the classic Fama–MacBeth two-step procedure, our model can achieve substantial efficiency gains for inference by adopting a one-step procedure using the entire sample rather than a single cross-sectional regression at each time point. We propose a local linear common correlated effects estimator for estimating time-varying betas by pooling the data. The consistency and asymptotic normality of the proposed estimators are established. Another methodological and empirical challenge in asset pricing is how to test the constancy of conditional betas and the significance of pricing errors, we echo this challenge by constructing an L2-norm statistic for functional-coefficient panel data models allowing for cross-sectional dependence. We show that the new test statistic has a limiting standard normal distribution under the null hypothesis. Finally, the method is applied to test the model in Fama and French (1993) using Fama–French 25 and 100 portfolios, sorted by size and book-to-market ratio, respectively, dated from July 1963 to July 2018.

On the identification of joint distributions using marginals and aggregates

A data combination approach is proposed to identify variables’ joint distribution when only their marginals and the distribution of their sum are known. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure. A variation of the well-known Lemma of Kotlarski (Kotlarski,1967) is established. Potential applications are proposed where aggregated data help identify within-household or longitudinal distributions in the absence of intra-household or panel data, respectively.

Measuring for management in science, technology, engineering, and mathematics learning ecosystems

Rapid global expansion of multi-stakeholder ecosystems for learning in Science, Technology, Engineering, and Mathematics (STEM) demand close attention to the information infrastructure needed for sharing best practices and improving outcomes. The existing conceptual model of ecosystem development and elements needs to be translated into a metrological measurement model tailored to ecosystem management. An evaluation tool not designed from measurement principles included 38 questions applied across three years. An initial review of the instrument conducted before data were made available found multiple ambiguous items and rating categories requiring respondents to summarize diverse aspects of their experience in a single rating, with no capacity to reconstruct which aspects were included by any given respondent. Response data from 36 ecosystems in 2016, 38 in 2017, and 110 in 2018 produced more uncertainty than expected given the numbers of items, rating scale categories, and responses. No common factor structures across items could be identified. Stated expectations already on the record concerning STEM ecosystem development characteristics and focal partners, attributes, and goal areas provide a basis for an instrument redesign likely to result in meaningful measures advancing a theory of action fit for the purpose of STEM learning ecosystem management.

Validity of the Center for Epidemiologic Studies Depression Scale (CES-D) in Eritrean refugees living in Ethiopia

BackgroundDepression is among the top mental health problems with a major contribution to the global burden of disease. This study aimed at identifying the latent factor structure and construct validity...

Quantile Co-Movement in Financial Markets: A Panel Quantile Model With Unobserved Heterogeneity

This article introduces a new procedure for analyzing the quantile co-movement of a large number of financial time series based on a large-scale panel data model with factor structures. The proposed method attempts to capture the unobservable heterogeneity of each of the financial time series based on sensitivity to explanatory variables and to the unobservable factor structure. In our model, the dimension of the common factor structure varies across quantiles, and the explanatory variables is allowed to depend on the factor structure. The proposed method allows for both cross-sectional and serial dependence, and heteroscedasticity, which are common in financial markets.We propose new estimation procedures for both frequentist and Bayesian frameworks. Consistency and asymptotic normality of the proposed estimator are established. We also propose a new model selection criterion for determining the number of common factors together with theoretical support.We apply the method to analyze the returns for over 6000 international stocks from over 60 countries during the subprime crisis, European sovereign debt crisis, and subsequent period. The empirical analysis indicates that the common factor structure varies across quantiles. We find that the common factors for the quantiles and the common factors for the mean are different. Supplementary materials for this article are available online.

Validation of an agent-specific safety climate model for construction

Purpose Safety climate (SC) is considered a leading indicator of safety performance, but scholars suggest that a common SC assessment framework is yet to be developed. Following the debate between the importance of facet analysis and agent analysis, the purpose of this paper is to test a factor structure, developed by the authors in previous work and arising from their systematic literature review, highlighting the role of safety agents in a construction site setting. Design/methodology/approach Multi-level SC surveys were conducted at five construction sites in Sydney, Australia, collecting data from of 352 workers associated with a mega-construction project. While examining the factor analysis of different studies, data reliability and data validity of the survey findings were ensured and a goodness-of-fit of SC model was examined through structural equation modelling. Findings The systematic literature review of Newaz et al. (2018) suggested a five-factor model of: management commitment, safety system, role of the supervisor, workers’ involvement and group SC. However, empirical data indicated that the questionnaire used to measure “safety system” failed to pass scale reliability; thus, a four-factor model was proposed to develop an agent-specific SC factor structure in the construction industry. Originality/value The four-factor model indicates the role and level of influence of different safety agents to improve safety perceptions on construction sites. The findings of this study will encourage researchers in construction safety to use the simplified four-factor SC (agent-specific) model presented and test it to further develop a common factor structure for the construction industry. The fact that the model is comprised of four factors makes further implementation somewhat easier in the development of safety plans, and when considering the role of safety agents, therefore enhancing its potential value.

An examination of the psychometric properties of the Connor-Davidson Resilience Scale-10 (CD-RISC10) among accounting and business students

Using a sample of 546 undergraduate accounting and business students from four US universities, one on the East Coast, two in the South, and one on the West Coast, this study examined the efficacy of the Connor-Davidson Resilience Scale-10 (Campbell-Sills & Stein, 2007; CD-RISC 10) for use with accounting and other designated business majors. The analyses included an examination of possible demographic differences in overall score, the scale’s factor structure, the invariance of its factor structure across major and gender, the scale’s reliability, and its convergent and divergent validity. The results indicate significant inter-major and gender differences in scores. Most troubling, female accounting majors report the lowest resilience levels, significantly below those recorded for male accounting majors, and male and female non-accounting majors. However, the scale has a common factor structure. We further find that a two-factor solution provides a superior fit to the data compared to the single factor structure used in most prior research. Spearman-Brown reliability coefficients, item-total correlations, and coefficient alphas each support the reliability of the items loading on the scale for the full sample, as well as for each of the above-referenced demographic subsamples.

A demographic and psychometric assessment of the Connor-Davidson resilience scale 10 (CD-RISC 10) with a US public accounting sample

PurposeThis paper aims to evaluate the efficacy of the Connor–Davidson Resilience Scale 10 (CD-RISC 10) (Campbell-Sills and Stein, 2007) for use in public accounting settings.Design/methodology/approachThe analyses include an examination of possible demographic differences in overall score, the scale’s factor structure, the invariance of its factor structure across gender and age groups, the scale’s reliability and its convergent and divergent validity.FindingsThere are significant gender and age group difference in scores, but a common univariate factor structure for the scale. The authors further find that a two-factor solution provides a superior fit to the data compared to the single factor structure used in the most prior research. Spearman–Brown reliability coefficients, item-total correlations and coefficient alphas each support the reliability of the items loading on the scale for the full sample, as well as for each of the above-referenced demographic subsamples.Research limitations/implicationsLimitations are acknowledged related to the use of self-report measures, absence of test-retest score comparisons and convergent and divergent assessments limited to the heterotrait–homomethod approach.Practical implicationsThe CD-RISC 10 is an expedient resilience measure, as it can be completed and scored in just a few minutes. Human resource administrators at public accounting firms can use it as an initial screening measure to identify staff who might benefit from resilience training. The paper adds to the appreciation of what not to do in the face of crisis by the government and those in charge of large accounting organizations.Social implicationsThe CD-RISC 10 can be used in research and clinical efforts to reduce voluntary turnover of audit staff and enhance the well-being of auditors in the workplace.Originality/valueThis study provides empirical evidence that the CD-RISC 10 is a valid and reliable measure for future assessments of auditor resilience levels.

A novel approach for testing the parity relationship between CDS and credit spread

We test the CDS-credit spread arbitrage by taking into account the presence of an unobserved common factor structure driving the movement in the prices. We examine 193 European CDS-Bond basis from January 2007 to December 2009. We estimate one and two common factors for the corporate bond spreads and the CDS premia, respectively. We address the issue of cross-member cointegration by adopting a novel approach. While standard cointegration techniques support the parity relation, the novel approach discards this hypothesis.

Developing a safety climate factor model in construction research and practice

PurposeSafety climate and its impact on safety performance is well established; however, researchers in this field suggest that the absence of a common assessment framework is a reflection of the state of development of this concept. The purpose of this paper is to propose a five-factor model that can be used to diagnose and measure safety climate in construction safety research and practice.Design/methodology/approachA systematic review was adopted, and following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 574 articles were selected at the start of the study based on a developed review protocol for investigating safety climate factors. While examining the factor analysis of different studies, data reliability and data validity of the individual research findings were considered and frequency of factors uploaded was used to determine the significance as a quantitative measure to develop the ranking of safety climate factors.FindingsThe review identified that, from the established measures of safety climate in construction, there is little uniformity on factor importance. However, management commitment safety system role of the supervisor; workers’ involvement and group safety climate were found to be the most common across the studies reviewed. It is proposed these factors are used to inform a five-factor model for investigating safety climate in the construction industry.Originality/valueThe findings of this study will motivate researchers and practitioners in safety to use the five-factor safety climate model presented in this paper and test it to develop a common factor structure for the construction industry. The fact that the model is comprised of five factors makes it easier to be used and implemented by small-to medium-sized construction companies, therefore enhancing its potential use.