scholarly journals Vingança e perdão: Dois lados de uma mesma moeda?

2020 ◽  
Vol 38 (2) ◽  
pp. 229-240
Author(s):  
Darlene Pinho Fernandes de Moura ◽  
Sophia Lóren De Holanda Sousa ◽  
Isabele Negreiros de Queiroz Pereira ◽  
Mariana Gonçalves Farias ◽  
Quésia Fernandes Cataldo ◽  
...  
Keyword(s):  
Higher Education ◽  
Factor Model ◽  
Common Factor ◽  
Empirical Support ◽  
Social Changes ◽  
Willingness To Forgive

The desire to punish someone who has caused suffering is characterized by revenge. However, it ispossible for someone to present pro-social changes in relation to the offender, which constitutesforgiveness. Studies point out that forgiveness and revenge can be understood in the opposite wayand also share a common dimension. In this sense, this study aimed to compare the adjustment of atwo-factor model for forgiveness and revenge with alternative explanations of one-factor and twofactormodels. 195 people participated, the majority female (66.7%), heterosexual (83.2%), single (80.8%), with incomplete higher education (68.4%) and with ages between 18 and 82 years (M=27.26; SD=11.50), who responded to the Willingness to Forgive Scale and the Vengeance Scale. The results showed that the two-factor model was more appropriate [χ2(102)=175.639, p<0.001; χ2/gl=1.54, SRMR=0.06, CFI=0.94, RMSEA=0.061 (CI90%=0.04-0.07), TLI=0.93]. The results found suggest that, in addition to sharing a common factor, the variables seem to have legitimacy as distinct constructs, providing empirical support for the promotion of strategies aimed at intervening in both general and specific elements related to the constructs.

Challenging the Multidimensional Conception of Perceived Person-Environment Fit

2020 ◽  
pp. 1-9
Author(s):  
Julian M. Etzel ◽  
Gabriel Nagy
Keyword(s):  
Higher Education ◽  
University Students ◽  
Educational Outcomes ◽  
Factor Model ◽  
Higher Order ◽  
Substantial Proportion ◽  
Unique Variance ◽  
First Order ◽  
Person Environment Fit ◽  
Order Factor

Abstract. In the current study, we examined the viability of a multidimensional conception of perceived person-environment (P-E) fit in higher education. We introduce an optimized 12-item measure that distinguishes between four content dimensions of perceived P-E fit: interest-contents (I-C) fit, needs-supplies (N-S) fit, demands-abilities (D-A) fit, and values-culture (V-C) fit. The central aim of our study was to examine whether the relationships between different P-E fit dimensions and educational outcomes can be accounted for by a higher-order factor that captures the shared features of the four fit dimensions. Relying on a large sample of university students in Germany, we found that students distinguish between the proposed fit dimensions. The respective first-order factors shared a substantial proportion of variance and conformed to a higher-order factor model. Using a newly developed factor extension procedure, we found that the relationships between the first-order factors and most outcomes were not fully accounted for by the higher-order factor. Rather, with the exception of V-C fit, all specific P-E fit factors that represent the first-order factors’ unique variance showed reliable and theoretically plausible relationships with different outcomes. These findings support the viability of a multidimensional conceptualization of P-E fit and the validity of our adapted instrument.

From Bi-Dimensionality to Uni-Dimensionality in Self-Report Questionnaires

2020 ◽  
pp. 1-14 ◽  
Author(s):  
Bjarne Schmalbach ◽  
Markus Zenger ◽  
Michalis P. Michaelides ◽  
Karin Schermelleh-Engel ◽  
Andreas Hinz ◽  
...  
Keyword(s):  
Factor Model ◽  
Common Factor ◽  
Self Regulation ◽  
Model Fit ◽  
Self Report ◽  
External Criterion ◽  
Common Factor Model ◽  
Random Intercept ◽  
Using Data ◽  
Core Self

Abstract. The common factor model – by far the most widely used model for factor analysis – assumes equal item intercepts across respondents. Due to idiosyncratic ways of understanding and answering items of a questionnaire, this assumption is often violated, leading to an underestimation of model fit. Maydeu-Olivares and Coffman (2006) suggested the introduction of a random intercept into the model to address this concern. The present study applies this method to six established instruments (measuring depression, procrastination, optimism, self-esteem, core self-evaluations, and self-regulation) with ambiguous factor structures, using data from representative general population samples. In testing and comparing three alternative factor models (one-factor model, two-factor model, and one-factor model with a random intercept) and analyzing differential correlational patterns with an external criterion, we empirically demonstrate the random intercept model’s merit, and clarify the factor structure for the above-mentioned questionnaires. In sum, we recommend the random intercept model for cases in which acquiescence is suspected to affect response behavior.

scholarly journals A Dynamic Factor and Neural Networks Analysis of the Co-movement of Public Revenues in the EMU

2021 ◽  
Author(s):  
Cosimo Magazzino ◽  
Marco Mele
Keyword(s):  
Neural Networks ◽  
Factor Model ◽  
Common Factor ◽  
Back Propagation ◽  
Dynamic Factor ◽  
Common Component ◽  
Economic Cycles ◽  
Composite Nature ◽  
Empirical Demonstration ◽  
Public Revenues

AbstractThis paper shows that the co-movement of public revenues in the European Monetary Union (EMU) is driven by an unobserved common factor. Our empirical analysis uses yearly data covering the period 1970–2014 for 12 selected EMU member countries. We have found that this common component has a significant impact on public revenues in the majority of the countries. We highlight this common pattern in a dynamic factor model (DFM). Since this factor is unobservable, it is difficult to agree on what it represents. We argue that the latent factor that emerges from the two different empirical approaches used might have a composite nature, being the result of both the more general convergence of the economic cycles of the countries in the area and the increasingly better tuned tax structure. However, the original aspect of our paper is the use of a back-propagation neural networks (BPNN)-DF model to test the results of the time-series. At the level of computer programming, the results obtained represent the first empirical demonstration of the latent factor’s presence.

Underlying Common Factors of Adolescent Problem Behaviors

2002 ◽  
Vol 29 (2) ◽  
pp. 161-182 ◽  
Author(s):  
Lening Zhang ◽  
John W. Welte ◽  
William F. Wieczorek
Keyword(s):  
Problem Behaviors ◽  
Latent Variable ◽  
Factor Model ◽  
Common Factor ◽  
Measurement Model ◽  
First Order ◽  
Adolescent Problem Behaviors ◽  
The Common ◽  
Order Factor ◽  
Second Order Factor Analysis

The Buffalo Longitudinal Study of Young Men was used to address the possibility of a common factor underlying adolescent problem behaviors. First, a measurement model with a single first-order factor was compared to a model with three separate correlated first-order factors. The three-factor model was better supported, making it logical to conduct a second-order factor analysis, which confirmed the logic. Second, a substantive model was estimated in each of two waves with psychopathic state as the common factor predicting drinking, drug use, and delinquency. Psychopathic state was stable across waves. The theory that a single latent variable accounts for large covariance among adolescent problem behaviors was supported.

scholarly journals Are Slovak Universities Prepared to Create the Department of Geragogy and Train Future Geragogues?

2019 ◽  
Vol 9 (1) ◽  
pp. 39-55
Author(s):  
Beáta Balogová ◽  
Veronika Kmetóny Gazdová
Keyword(s):  
Higher Education ◽  
Older Adult ◽  
Public Institutions ◽  
Institutions Of Higher Education ◽  
Social Changes ◽  
Adult Educator ◽  
Undergraduate Training ◽  
Study Program ◽  
Older Adult Education ◽  
Definition Of

Abstract Introduction:The authors of this paper base their research on the following assumption: the development of both geragogic education (older adult education) and profession is conditioned by the existence of a study program of geragogy provided by departments of geragogy created at universities (as public institutions of higher education). The fact remains that a qualified training of geragogues is absent in the Slovak conditions. Purpose:When compiling a graduate profile, inclusive of a list of competences that a geragogue should possess, a range of specific local circumstances needs to be taken into consideration. Subsequently, it is necessary to define a position of a geragogue. Geragogue is a professional working in the field of senior education, just like a pedagogue or an adult educator work in their fields. It is also important to identify and accentuate the philosophical and social context in which these professionals are confronted with the demands of today’s society, in a form of a society based on knowledge, questions of the ongoing social changes and defining the meaning of life. Results:The task of creating the department and program of geragogy is formulated as a social demand of the time, debunking the current myth of the crisis of universities. In history, a university was a vital place where the values serving social integration emerged. It was also a practice field for the educators to train so they could spread these values and transform them into social skills. Conclusion:In the conclusion, the authors propose key areas of undergraduate training of geragogues, including the definition of institutional anchoring, with the goal to contribute to ongoing professional discussion and to creation of the department and the program of geragogy.

Item Response Theory Analysis to Assess Dimensionality of Substance Use Disorder Abuse and Dependence Symptoms

2017 ◽  
Vol 6 (4) ◽  
Author(s):  
Levent Kirisci ◽  
Ralph Tarter ◽  
Maureen Reynolds ◽  
Michael Vanyukov
Keyword(s):  
Substance Use ◽  
Item Response Theory ◽  
Item Response ◽  
Substance Use Disorder ◽  
Factor Model ◽  
Common Factor ◽  
Latent Trait ◽  
Dominant Factor ◽  
Response Theory ◽  
Men And Women

Background. Item response theory (IRT) based studies conducted on diverse samples showed a single dominant factor for DSM-III-R and DSM-IV substance use disorder (SUD) abuse and dependence symptoms of alcohol, cannabis, sedative, cocaine, stimulants, and opiates use disorders. IRT provides the opportunity, within a person-centered framework, to accurately gauge each person’s severity of disorder that, in turn, informs required intensiveness of treatment. Objectives. The aim of this study was to determine whether the SUD symptoms indicate a unidimensional trait or instead need to be conceptualized and quantified as a multidimensional scale. Methods. The sample was composed of families of adult SUD+ men (n=349), and SUD+ women (n=173), who qualified for DSM-III-R diagnosis of substance use disorder (abuse or dependence) and families of adult men and women who did not qualify for a SUD diagnosis (SUD- men: n=190, SUD- women: n=133). An expanded version of the Structured Clinical Interview for DSM-III-R (SCID) was administered to characterize lifetime and current substance use disorders. Item response theory methodology was used to assess the dimensionality of DSM-III-R SUD abuse and dependence symptoms.Results. A bi-factor model provided the optimal representation of the factor structure of SUD symptoms in males and females. SUD symptoms are scalable as indicators of a single common factor, corresponding to general (non-drug-specific, common) liability to addiction, combined with drug-specific liabilities. Conclusions. IRT methodology used to quantify the continuous general liability to addiction (GLA) latent trait in individuals having SUD symptoms was found effective for accurately measuring SUD severity in men and women. This may be helpful for person-centered medicine approaches to effectively address intensity of treatment.

scholarly journals Generalized Mean-Reverting 4/2 Factor Model

2019 ◽  
Vol 12 (4) ◽  
pp. 159 ◽  
Author(s):  
Yuyang Cheng ◽  
Marcos Escobar-Anel ◽  
Zhenxian Gong
Keyword(s):  
Value At Risk ◽  
Implied Volatility ◽  
Factor Model ◽  
Risk Measures ◽  
Risk Measure ◽  
Common Factor ◽  
Principal Component ◽  
Characteristic Functions ◽  
Implied Volatility Surface ◽  
Volatility Surface

This paper proposes and investigates a multivariate 4/2 Factor Model. The name 4/2 comes from the superposition of a CIR term and a 3/2-model component. Our model goes multidimensional along the lines of a principal component and factor covariance decomposition. We find conditions for well-defined changes of measure and we also find two key characteristic functions in closed-form, which help with pricing and risk measure calculations. In a numerical example, we demonstrate the significant impact of the newly added 3/2 component (parameter b) and the common factor (a), both with respect to changes on the implied volatility surface (up to 100%) and on two risk measures: value at risk and expected shortfall where an increase of up to 29% was detected.

Measuring Statistics Attitudes at the Student and Instructor Levels: A Multilevel Construct Validity Study of the Survey of Attitudes Toward Statistics

2020 ◽  
pp. 073428292097138
Author(s):  
Chao Xu ◽  
Candace Schau
Keyword(s):  
Student Development ◽  
Large Scale ◽  
Factor Model ◽  
Empirical Support ◽  
Educational Practice ◽  
Large Scale Assessment ◽  
Multilevel Confirmatory Factor Analysis ◽  
Teacher Student ◽  
Teaching Characteristics ◽  
Attitudes Toward Statistics

Numerous studies have been conducted using the Survey of Attitudes Toward Statistics-36 (SATS-36). Recently, large-scale assessment studies have begun to examine the extent to which students vary in their statistics attitudes across instructors. Yet, empirical evidence linking student responses to the SATS items to instructor-level constructs is still lacking. Using multilevel confirmatory factor analysis, we investigated the factor structure underlying the measure of students’ statistics attitudes at both the student and instructor levels. Results from 13,507 college students taught by 160 introductory statistics instructors support a correlated six-factor model at each level. Additionally, there is evidence for the structural validity of a shared teacher–student attitude impacts construct that may capture meaningful patterns of teaching characteristics and competencies tied to student development of statistics attitudes. These findings provide empirical support for the use of the SATS-36 in studying contextual variables in relation to statistics instructors. Implications for educational practice are discussed.

Structural Equation Modeling with Factors and Composites

2017 ◽  
Vol 13 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Factor Model ◽  
Common Factor ◽  
Equation Modeling ◽  
A Algorithm ◽  
Multivariate Statistical ◽  
Full Information Maximum Likelihood ◽  
Common Factor Model ◽  
Path Coefficients

Recent methodological developments building on partial least squares (PLS) techniques and related ideas have significantly contributed to bridging the gap between factor-based and composite-based structural equation modeling (SEM) methods. PLS-SEM is extensively used in the field of e-collaboration, as well as in many other fields where multivariate statistical analyses are employed. The author compares results obtained with four methods: covariance-based SEM with full information maximum likelihood (FIML), factor-based SEM with common factor model assumptions (FSEM1), factor-based SEM building on the PLS Regression algorithm (FSEM2), and PLS-SEM employing the Mode A algorithm (PLSA). The comparison suggests that FSEM1 yields path coefficients and loadings that are very similar to FIML's; and that FSEM2 yields path coefficients that are very similar to FIML's and loadings that are very similar to PLSA's.

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