914 resultados para Three Factor Model
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This paper is on a simulation for offshore wind systems in deep water under cloud scope. The system is equipped with a permanent magnet synchronous generator and a full-power three-level converter, converting the electric energy at variable frequency in one at constant frequency. The control strategies for the three-level are based on proportional integral controllers. The electric energy is injected through a HVDC transmission submarine cable into the grid. The drive train is modeled by a three-mass model taking into account the resistant stiffness torque, structure and tower in the deep water due to the moving surface elevation. Conclusions are taken on the influence of the moving surface on the energy conversion. © IFIP International Federation for Information Processing 2015.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics and Maastricht University School of Business and Economics
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Tese de Doutoramento em Ciências Empresariais.
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There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors.
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This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and volatilities, and our model averaging method allows for investors' model uncertainty over time. Our time-varying parameter Nelson-Siegel Dynamic Model Averaging (NS-DMA) predicts yields better than standard benchmarks and successfully captures plausible time-varying term premia in real time. The proposed model has significant in-sample and out-of-sample predictability for excess bond returns, and the predictability is of economic value.
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Glutaric aciduria type I (glutaryl-CoA dehydrogenase deficiency) is an inborn error of metabolism that usually manifests in infancy by an acute encephalopathic crisis and often results in permanent motor handicap. Biochemical hallmarks of this disease are elevated levels of glutarate and 3-hydroxyglutarate in blood and urine. The neuropathology of this disease is still poorly understood, as low lysine diet and carnitine supplementation do not always prevent brain damage, even in early-treated patients. We used a 3D in vitro model of rat organotypic brain cell cultures in aggregates to mimic glutaric aciduria type I by repeated administration of 1 mM glutarate or 3-hydroxyglutarate at two time points representing different developmental stages. Both metabolites were deleterious for the developing brain cells, with 3-hydroxyglutarate being the most toxic metabolite in our model. Astrocytes were the cells most strongly affected by metabolite exposure. In culture medium, we observed an up to 11-fold increase of ammonium in the culture medium with a concomitant decrease of glutamine. We further observed an increase in lactate and a concomitant decrease in glucose. Exposure to 3-hydroxyglutarate led to a significantly increased cell death rate. Thus, we propose a three step model for brain damage in glutaric aciduria type I: (i) 3-OHGA causes the death of astrocytes, (ii) deficiency of the astrocytic enzyme glutamine synthetase leads to intracerebral ammonium accumulation, and (iii) high ammonium triggers secondary death of other brain cells. These unexpected findings need to be further investigated and verified in vivo. They suggest that intracerebral ammonium accumulation might be an important target for the development of more effective treatment strategies to prevent brain damage in patients with glutaric aciduria type I.
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According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.
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The purpose of this study was to evaluate the factor structure and the reliability of the French versions of the Identity Style Inventory (ISI-3) and the Utrecht-Management of Identity Commitments Scale (U-MICS) in a sample of college students (N = 457, 18 to 25 years old). Confirmatory factor analyses confirmed the hypothesized three-factor solution of the ISI-3 identity styles (i.e. informational, normative, and diffuse-avoidant styles), the one-factor solution of the ISI-3 identity commitment, and the three-factor structure of the U-MICS (i.e. commitment, in-depth exploration, and reconsideration of commitment). Additionally, theoretically consistent and meaningful associations among the ISI-3, U-MICS, and Ego Identity Process Questionnaire (EIPQ) confirmed convergent validity. Overall, the results of the present study indicate that the French versions of the ISI-3 and UMICS are useful instruments for assessing identity styles and processes, and provide additional support to the cross-cultural validity of these tools.
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Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data
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We have examined the internal validity of the French translation of the NEO PI-R personality test which measures the « big five » (Rolland, 1993). The impact of age, gender and professional categories on the NEO PI-R scales was assessed. A large sample (n=731) of subjects of different age, gender and profession and a sample of Swiss students (n=261) responding anonymously were used. Factor analyses confirmed the structure of the instrument (5 domains) and the structures of the domains in terms of facets (six facets within each domain). On the other hand, the age has a significant impact on all the domains of the NEO PI-R; the gender has an impact on the scores on N (neuroticism), O (openness) and A (agreeableness), and the profession has an impact on the domains E (extraversion), O (openness) and A (agreeableness). The scores on several facets are also affected by those three variables. Our study gives the researchers and the practitioner a reference score table according to the studied variables.
Validation d'une version abrégée du TCI (TCI-56) sur un échantillon de jeunes fumeurs et non-fumeurs
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Introduction: The psychobiological seven-factor model proposed by Cloninger et al. (1993) takes into account temperament and character dimensions to describe personality. Four of the dimensions are linked with biological, genetic and neuroanatomic structures, whereas the three other dimensions are related to the degree of individual, social and spiritual development. A study conducted by Wills et al. (1994) with adolescents showed that substance abuse was associated with high scores on Novelty Seeking and low scores on Harm Avoidance and Reward Dependence. The aim of the present study was, firstly, to create a short form of Cloninger's (1993) Temperament and Character Inventory (TCI) and, secondly, to study the impact of nicotine dependence as well as demographic variables on a sample of young adults. Method: We created a short form of the TCI containing 56 items (TCI-56), 8 for each scale. Responses are made on a five-point Likert type scale. A Swiss sample (n=211), of 116 women and 95 men, aged from 15 to 30 years, participated in this study. Our population was divided into a group of 81 smokers and another of 130 non-smokers, according to their scores on the Fagerstörm test for nicotine dependence (1999). Results: The structural validation consisted of two separate factor analysis with varimax rotations, one for the temperamental items, and the other, for the character ones. The first factor analysis conducted on the items of the temperament scales allowed to extract 4 factors explaining 40.7% of the variance. The correlations between factors and scales are the following: r=.71 for Novelty Seeking, r=.69 for Persistence, r=.95 for Harm Avoidance, r=.94 for Reward Dependence. The second factor analysis conducted on the items of the character scales allowed to extract 3 factors explaining 41.5% of the variance. The correlations between factors and scales are the following: r=.94 for Self-Directedness, r=.91 for Cooperativeness and r=.99 for Self-Transcendence. The internal consistencies range from α=.65 to α=.75 for the temperament scales, and from α=.71 to α=.83 for the three character scales. Concerning, the impact of the nicotine dependence, we observed that smokers have significantly higher scores for Novelty seeking, than non-smokers (p=.01). We found no difference for Harm Avoidance and Reward Dependence. Nevertheless, smokers seem to have the tendency to score higher on Transcendence (p=.06). Moreover, people having smoked more than 100 cigarettes in their life have significantly higher scores on this scale (p.04) and the correlation between Transcendence and the Fagerstörm test is significant (r=.19). We also found gender differences: the women (N=116) obtain significantly higher scores for Harm Avoidance (p<.001), for Reward Dependence (p<.001) and for Cooperation (p=.01). We further found a significant correlation between age and Self-Directedness, r=.34. We observed no interaction between gender and smoking or age and smoking on the dimensions of the TCI-56. Discussion: The TCI short form (TCI-56) seems to be a valid and useful inventory to assess personality differences. Confirming the results of others about the relation between addiction and personality, we found that smokers have significantly higher scores for Novelty seeking, than non-smokers. But we were not able to find any significant differences for Harm Avoidance and Reward Dependence. This might be due to our sample that was made of young adults. This study also shows that Transcendence could be an interesting dimension for studies on Tobacco smoking to consider. Concerning the impact of demographic variables, we observed that age and gender have specific and coherent influence on personality.
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Three different short versions of the NEO-PI-R were compared: The NEO-FFI, the NEO-FFI-R, and a new short version developed in the current study (NEO-60). This new version is intended to improve the psychometric characteristics of the original NEO-FFI, specially in regard to the factor structure at the item-level. A French version of the NEO-PI-R was given to 1090 Swiss subjects, whereas the Spanish (Castilian) version of the NEO-PI-R was administered to 1006 Spanish subjects. Results replicate the limitations of the NEO-FFI already found in other countries. Compared to the NEO-FFI, reliability coefficients and factor structure was enhanced by the NEO-FFI-R and the NEO-60 in both samples, although substantial differences were not found. The factor structure of the NEO-60 shows the best fit since only three items do not load mainly on their own factor in both samples. Besides, correlations between items and NEO-PI-R domain scores are also higher for the items included in the NEO-60 version. On the other hand, convergent correlations with the NEO-PI-R dimensions were satisfactory irrespective of the version, and confirmatory factor analyses show slight differences among the different models generated after the three short versions.
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Aims: To describe personality traits and their changes in mild cognitive impairment (MCI) and control subjects. Methods: Sixty-three MCI and 90 control subjects were asked to describe their current personality traits by the Structured Interview for the Five-Factor Model (SIFFM). For each subject, a close relative retrospectively assessed these descriptions both as to the previous and current personality traits, using the Revised NEO Personality Inventory, Form R (NEO-PI-R). Results: Self-assessed MCI subjects reported significantly lower scores in the openness dimension than control subjects [F(1, 150) = 9.84, p = 0.002, ηp(2) = 0.06]. In current observer ratings, MCI subjects had higher scores on neuroticism [F(1, 137) = 7.55, p = 0.007, ηp(2) = 0.05] and lower ones on extraversion [F(1, 137) = 6.40, p = 0.013, ηp(2) = 0.04], openness [F(1, 137) = 9.93, p = 0.002, ηp(2) = 0.07], agreeableness [F(1, 137) = 10.18, p = 0.002, ηp(2) = 0.07] and conscientiousness [F(1, 137) = 25.96, p < 0.001, ηp(2) = 0.16]. Previous personality traits discriminated the groups as previous openness [odds ratio (OR) = 0.97, 95% confidence interval (CI) = 0.95-0.99, p = 0.014] and conscientiousness (OR = 0.96, 95% CI 0.94-0.98, p = 0.001) were negatively related to MCI group membership. In MCI subjects, conscientiousness [F(1, 137) = 19.20, p < 0.001, ηp(2) = 0.12] and extraversion [F(1, 137) = 22.27, p < 0.001, ηp(2) = 0.14] decreased between previous and current evaluations and neuroticism increased [F(1, 137) = 22.23, p < 0.001, ηp(2) = 0.14], whereas no significant change was found in control subjects. Conclusions: MCI subjects undergo significant personality changes. Thus, personality assessment may aid the early detection of dementia. © 2013 S. Karger AG, Basel.
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BACKGROUND CONTEXT: Studies involving factor analysis (FA) of the items in the North American Spine Society (NASS) outcome assessment instrument have revealed inconsistent factor structures for the individual items. PURPOSE: This study examined whether the factor structure of the NASS varied in relation to the severity of the back/neck problem and differed from that originally recommended by the developers of the questionnaire, by analyzing data before and after surgery in a large series of patients undergoing lumbar or cervical disc arthroplasty. STUDY DESIGN/SETTING: Prospective multicenter observational case series. PATIENT SAMPLE: Three hundred ninety-one patients with low back pain and 553 patients with neck pain completed questionnaires preoperatively and again at 3 to 6 and 12 months follow-ups (FUs), in connection with the SWISSspine disc arthroplasty registry. OUTCOME MEASURES: North American Spine Society outcome assessment instrument. METHODS: First, an exploratory FA without a priori assumptions and subsequently a confirmatory FA were performed on the 17 items of the NASS-lumbar and 19 items of the NASS-cervical collected at each assessment time point. The item-loading invariance was tested in the German version of the questionnaire for baseline and FU. RESULTS: Both NASS-lumbar and NASS-cervical factor structures differed between baseline and postoperative data sets. The confirmatory analysis and item-loading invariance showed better fit for a three-factor (3F) structure for NASS-lumbar, containing items on "disability," "back pain," and "radiating pain, numbness, and weakness (leg/foot)" and for a 5F structure for NASS-cervical including disability, "neck pain," "radiating pain and numbness (arm/hand)," "weakness (arm/hand)," and "motor deficit (legs)." CONCLUSIONS: The best-fitting factor structure at both baseline and FU was selected for both the lumbar- and cervical-NASS questionnaires. It differed from that proposed by the originators of the NASS instruments. Although the NASS questionnaire represents a valid outcome measure for degenerative spine diseases, it is able to distinguish among all major symptom domains (factors) in patients undergoing lumbar and cervical disc arthroplasty; overall, the item structure could be improved. Any potential revision of the NASS should consider its factorial structure; factorial invariance over time should be aimed for, to allow for more precise interpretations of treatment success.
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The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.