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2022 ◽  
Vol 15 (1) ◽  
pp. 14
Author(s):  
Richard T. Baillie ◽  
Fabio Calonaci ◽  
George Kapetanios

This paper presents a new hierarchical methodology for estimating multi factor dynamic asset pricing models. The approach is loosely based on the sequential Fama–MacBeth approach and developed in a kernel regression framework. However, the methodology uses a very flexible bandwidth selection method which is able to emphasize recent data and information to derive the most appropriate estimates of risk premia and factor loadings at each point in time. The choice of bandwidths and weighting schemes are achieved by a cross-validation procedure; this leads to consistent estimators of the risk premia and factor loadings. Additionally, an out-of-sample forecasting exercise indicates that the hierarchical method leads to a statistically significant improvement in forecast loss function measures, independently of the type of factor considered.


2021 ◽  
Author(s):  
Nagisa Sugaya ◽  
Yoshitoshi Tomita ◽  
Misako Funaba ◽  
Hiroshi Iida ◽  
Kentaro Shirotsuki ◽  
...  

Abstract BackgroundThe Cognitive Scale for Functional Bowel Disorders (CS-FBD) is a useful measure to assess maladaptive cognition, and focuses on how functional bowel disorders relate to negative thoughts, perfectionism, and social desirability. This study aimed to confirm the reliability and validity of the Japanese version of the CS-FBD (CS-FBD-J). MethodsParticipants comprised 192 students (20.2±3.0 years) and 22 outpatients diagnosed with irritable bowel syndrome (IBS) (38.0±13.0 years). There were 76 students who met the diagnostic criteria for IBS, and two students who received treatment for IBS. Participants completed questionnaires containing the CS-FBD-J, IBS Severity Index (IBS-SI), Visceral Sensitivity Index (VSI), 24-item Dysfunctional Attitudes Scale (DAS-24), and Hospital Anxiety and Depression Scale (HADS).ResultsOur factor analysis revealed that the CS-FBD-J had a unidimensional factor structure, and that the factor loadings for 2 out of the 25 items were less than 0.4. After excluding the two items from the analysis, a single factor of the 23-item version accounted for 45.85% of the total variance. The CS-FBD-J scores had significant moderate correlations with the IBS-SI (r = 0.492~0.574) and VSI (r = 0.531~ 0.557) scores in the IBS group and the control group. Correlation between the DAS-24 and the CS-FBD-J was not significant (r = 0.179 ~ 0.191). Although the CS-FBD-J in the IBS group was significantly correlated with HADS-anxiety (r = 0.450) and depression scores (r = 0.357), their intercorrelations in the control group were not significant (r = 0.150 ~ 0.167). In the score comparison of the CS-FBD-J between the IBS patient group, non-patient IBS group (students with IBS except two who received treatment), and control group, there were significant group effects in the CS-FBD-J (IBS patient > non-patient IBS > control). The internal consistencies of the CS-FBD-J were high (α = 0.95). The item-total correlation analysis for the CS-FBD-J showed that the correlations between each item and the total score were significant.ConclusionThis study confirmed the reliability and validity of the 23-item version of the CS-FBS with the deletion of two items with low factor loadings.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12610
Author(s):  
Maryam Kazemitabar ◽  
Danilo Garcia ◽  
JohnBosco C. Chukwuorji ◽  
Ricardo Sanmartín ◽  
Franco Lucchese ◽  
...  

Background School health programs need to target all aspects of physical, psychological, and social well-being. Using a slightly modified version of the COSMIN Risk of Bias checklist, we developed and conducted the first validation of the School Health Assessment Tool for Primary Schools (SHAT-PS). Method The exploratory sequential mixed method was used in this study. In the first phase, scientific databases were systematically searched to find school health models and instruments and 65 interviews were conducted with school stakeholders. The Colaizzi’s method was used to code the qualitative data into themes. Then, a pool of items was created for each theme, rechecked by psychometric experts and then validated for content (i.e., relevance, clarity, and comprehensiveness) by psychometric experts and individuals of the target population (i.e., school personnel). In the second phase, classical test theory was utilized to analyze the validity and reliability of the resulting items from phase 1 among 400 individuals working at primary schools. Results The coding of the interviews resulted in ten themes that we labeled based on the theoretical literature: school health policies, community connections, health education, physical activity, health services, nutrition, psychological services, physical environment, equipment and facilities, and school staff’s health. The items created for each theme ended up in an initial pool of 76 items. In the final stage of phase 1, 69 items remained after the content validity assessment by experts and school personnel. In phase 2, the SHAT-PS items were tested using maximum likelihood exploratory factor analysis and confirmatory factor analysis. Of the 69 items from phase 1, 22 items were removed due to low factor loadings. The results showed that the 8-factor model was the best solution (chi-square/df = 2.41, CFI = .98, TLI = .97, RMSEA = .06). The discriminant and convergent validity of the SHAT-PS were evaluated as satisfactory and the scale had high internal consistency (Cronbach’s alpha for all subscales > .93). The test-retest reliability was satisfactory—the intraclass correlation coefficient pooled was .95 (99% CI [.91–.98]). Moreover, the standard error of measurement resulted in an SEM pooled equal to 4.4. No discrepancy was found between subgroups of gender and subgroups of staffs’ positions at schools. Conclusion The SHAT-PS is a valid and reliable tool that may facilitate school staff, stakeholders and researchers to evaluate the presence of the factors that promote health at primary schools. Nevertheless, in the process of validation, many of the items related to staff’s health were eliminated due to poor factor loadings. Obviously, staff health is an important factor in the measurement of school health. Hence, we recommend that the validity and reliability of the SHAT-PS in other cultures should be done using the original 76-item version.


Author(s):  
Tanya McCance ◽  
Brendan McCormack ◽  
Paul Slater ◽  
Donna McConnell

Research relating to person-centred practice continues to expand and currently there is a dearth of statistical evidence that tests the validity of an accepted model for person-centred practice. The Person-centred Practice Framework is a midrange theory that is used globally, across a range of diverse settings. The aim of this study was to statistically examine the relationships within the Person-centred Practice Framework. A cross sectional survey design using a standardized tool was used to assess a purposive sample (n = 1283, 31.8%) of multi-disciplinary health professionals across Ireland. Survey construct scores were included in a structural model to examine the theoretical model of person-centred practice. The results were drawn from a multi-disciplinary sample, and represented a broad range of clinical settings. The model explains 60.5% of the total variance. Factor loadings on the second order latent construct, along with fit statistics, confirm the acceptability of the measurement model. Statistically significant factor loadings were also acceptable. A positive, statistically significant relationship was observed between components of the Person-centred Practice Framework confirming it’s theoretical propositions. The study provides statistical evidence to support the Person-centred Practice Framework, with a multidisciplinary sample. The findings help confirm the effectiveness of the Person-Centred Practice Index for-Staff as an instrument that is theoretically aligned to an internationally recognised model for person-centred practice.


2021 ◽  
Author(s):  
Alicia Franco-Martínez ◽  
Jesús M. Alvarado ◽  
Miguel A. Sorrel

A sample suffers range restriction (RR) when its variance is reduced comparing to its population variance and, in turn, it fails representing such population. If the RR occurs over the latent factor, not directly over the observed variable, the researcher deals with an indirect RR, common when using convenience samples. This work explores how this problem affects different outputs of the factor analysis: multivariate normality (MVN), estimation process, goodness-of-fit, recovery of factor loadings, and reliability. In doing so, a Monte Carlo study was conducted. Data were generated following the linear selective sampling model, simulating tests varying their sample size (N = 200 and 500 cases), test size (J = 6, 12, 18, 24 items), loading size (L = .50, .70, and .90) and restriction size (from R = 1, .90, .80, and so on till .10 selection ratio). Our results systematically suggest that an interaction between decreasing the loading size and increasing the restriction size affects the MVN assessment, obstructs the estimation process, and leads to an underestimation of the factor loadings and reliability. However, most of the MVN tests and most of the fit indices employed were nonsensitive to the RR problem. We provide some recommendations to applied researchers.


Assessment ◽  
2021 ◽  
pp. 107319112110602
Author(s):  
Manuel Heinrich ◽  
Christian Geiser ◽  
Pavle Zagorscak ◽  
G. Leonard Burns ◽  
Johannes Bohn ◽  
...  

Symmetrical bifactor models are frequently applied to diverse symptoms of psychopathology to identify a general P factor. This factor is assumed to mark shared liability across all psychopathology dimensions and mental disorders. Despite their popularity, however, symmetrical bifactor models of P often yield anomalous results, including but not limited to nonsignificant or negative specific factor variances and nonsignificant or negative factor loadings. To date, these anomalies have often been treated as nuisances to be explained away. In this article, we demonstrate why these anomalies alter the substantive meaning of P such that it (a) does not reflect general liability to psychopathology and (b) differs in meaning across studies. We then describe an alternative modeling framework, the bifactor-( S−1) approach. This method avoids anomalous results, provides a framework for explaining unexpected findings in published symmetrical bifactor studies, and yields a well-defined general factor that can be compared across studies when researchers hypothesize what construct they consider “transdiagnostically meaningful” and measure it directly. We present an empirical example to illustrate these points and provide concrete recommendations to help researchers decide for or against specific variants of bifactor structure.


2021 ◽  
Vol 111 (11) ◽  
pp. 3575-3610
Author(s):  
Bruno Biais ◽  
Johan Hombert ◽  
Pierre-Olivier Weill

Incentive problems make securities’ payoffs imperfectly pledgeable, limiting agents’ ability to issue liabilities. We analyze the equilibrium consequences of such endogenous incompleteness in a dynamic exchange economy. Because markets are endogenously incomplete, agents have different intertemporal marginal rates of substitution, so that they value assets differently. Consequently, agents hold different portfolios. This leads to endogenous markets segmentation, which we characterize with optimal transport methods. Moreover, there is a basis going always in the same direction: the price of a security is lower than that of replicating portfolios of long positions. Finally, equilibrium expected returns are concave in factor loadings. (JEL D51, D52, G11, G12)


Author(s):  
Karl Schweizer ◽  
Andreas Gold ◽  
Dorothea Krampen

We investigated whether dichotomous data showed the same latent structure as the interval-level data from which they originated. Given constancy of dimensionality and factor loadings reflecting the latent structure of data, the focus was on the variance of the latent variable of a confirmatory factor model. This variance was shown to summarize the information provided by the factor loadings. The results of a simulation study did not reveal exact correspondence of the variances of the latent variables derived from interval-level and dichotomous data but shrinkage. Since shrinkage occurred systematically, methods for recovering the original variance were fleshed out and evaluated.


2021 ◽  
Vol 12 ◽  
Author(s):  
Chia-Wen Chen ◽  
Wen-Chung Wang ◽  
Magdalena Mo Ching Mok ◽  
Ronny Scherer

Compositional items – a form of forced-choice items – require respondents to allocate a fixed total number of points to a set of statements. To describe the responses to these items, the Thurstonian item response theory (IRT) model was developed. Despite its prominence, the model requires that items composed of parts of statements result in a factor loading matrix with full rank. Without this requirement, the model cannot be identified, and the latent trait estimates would be seriously biased. Besides, the estimation of the Thurstonian IRT model often results in convergence problems. To address these issues, this study developed a new version of the Thurstonian IRT model for analyzing compositional items – the lognormal ipsative model (LIM) – that would be sufficient for tests using items with all statements positively phrased and with equal factor loadings. We developed an online value test following Schwartz’s values theory using compositional items and collected response data from a sample size of N = 512 participants with ages from 13 to 51 years. The results showed that our LIM had an acceptable fit to the data, and that the reliabilities exceeded 0.85. A simulation study resulted in good parameter recovery, high convergence rate, and the sufficient precision of estimation in the various conditions of covariance matrices between traits, test lengths and sample sizes. Overall, our results indicate that the proposed model can overcome the problems of the Thurstonian IRT model when all statements are positively phrased and factor loadings are similar.


2021 ◽  
Author(s):  
Katharina Groskurth ◽  
Matthias Bluemke ◽  
Clemens M. Lechner

To evaluate model fit in confirmatory factor analysis, researchers compare goodness-of-fit indices (GOFs) against fixed cutoff values derived from simulation studies. However, these cutoffs may not be as broadly applicable as researchers typically assume, especially when used in settings not covered in the simulation scenarios from which these cutoffs were derived. Thus, we aim to evaluate (1) the sensitivity of GOFs to model misspecification and (2) their susceptibility to extraneous data and analysis characteristics (i.e., estimator, number of indicators, number of response options, distribution of response options, loading magnitude, sample size, and factor correlation). Our study includes the most comprehensive simulation on that matter to date. This enables us to uncover several previously unknown or at least underappreciated issues with GOFs. All widely used GOFs are far more susceptible to extraneous influences in even more complex ways than generally appreciated, and their sensitivity to misspecifications in factor loadings and factor correlations varies significantly across different scenarios. For instance, one of those strong influences on all GOFs constituted the magnitude of factor loadings (either as a main effect or two-way interaction with other characteristics). The strong susceptibility of GOFs to data and analysis characteristics showed that the practice of judging the fit of models against fixed cutoffs is more problematic than so-far assumed. Hitherto unnoticed effects on GOFs imply that no general cutoff rules can be applied to evaluate model fit. We discuss alternatives for assessing model fit and develop a new approach to tailor cutoffs for GOFs to research settings.


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