Curved Exponential Models in Econometrics

1997 ◽  
Vol 13 (6) ◽  
pp. 771-790 ◽  
Author(s):  
Kees Jan van Garderen
Keyword(s):  
Structural Equation ◽  
Equation Model ◽  
Econometric Models ◽  
Demand Systems ◽  
Likelihood Ratios ◽  
Sufficient Statistics ◽  
Sufficient Statistic ◽  
Exponential Models ◽  
Minimal Sufficient Statistic ◽  
The Difference

Curved exponential models have the property that the dimension of the minimal sufficient statistic is larger than the number of parameters in the model. Many econometric models share this feature. The first part of the paper shows that, in fact, econometric models with this property are necessarily curved exponential. A method for constructing an explicit set of minimal sufficient statistics, based on partial scores and likelihood ratios, is given. The difference in dimension between parameterand statistic and the curvature of these models have important consequences for inference. It is not the purpose of this paper to contribute significantly to the theory of curved exponential models, other than to show that the theory applies to many econometric models and to highlight some multivariate aspects. Using the methods developed in the first part, we show that demand systems, the single structural equation model, the seemingly unrelated regressions, and autoregressive models are all curved exponential models.

scholarly journals An Association Between Montessori Education in Childhood and Adult Wellbeing

2021 ◽  
Vol 12 ◽  
Author(s):  
Angeline S. Lillard ◽  
M. Joseph Meyer ◽  
Dermina Vasc ◽  
Eren Fukuda
Keyword(s):  
Private School ◽  
Structural Equation ◽  
Social Trust ◽  
Measurement Model ◽  
Equation Model ◽  
Large Set ◽  
Life Outcomes ◽  
Confirmatory Factor Analyses ◽  
Self Confidence ◽  
The Difference

Wellbeing, or how people think and feel about their lives, predicts important life outcomes from happiness to health to longevity. Montessori pedagogy has features that enhance wellbeing contemporaneously and predictively, including self-determination, meaningful activities, and social stability. Here, 1905 adults, ages 18–81 (M = 36), filled out a large set of wellbeing scales followed by demographic information including type of school attended each year from 2 to 17. About half the sample had only attended conventional schools and the rest had attended Montessori for between 2 and 16 years (M = 8 years). To reduce the variable set, we first developed a measurement model of wellbeing using the survey data with exploratory then confirmatory factor analyses, arriving at four factors: general wellbeing, engagement, social trust, and self-confidence. A structural equation model that accounted for age, gender, race, childhood SES, and years in private school revealed that attending Montessori for at least two childhood years was associated with significantly higher adult wellbeing on all four factors. A second analysis found that the difference in wellbeing between Montessori and conventional schools existed even among the subsample that had exclusively attended private schools. A third analysis found that the more years one attended Montessori, the higher one’s wellbeing as an adult. Unmeasured selection effects could explain the results, in which case research should determine what third variable associated with Montessori schooling causes adult wellbeing. Several other limitations to the study are also discussed. Although some of these limitations need to be addressed, coupled with other research, including studies in which children were randomly assigned to Montessori schools, this study suggests that attending Montessori as a child might plausibly cause higher adult wellbeing.

scholarly journals IMPACT OF GENDER DIVERSITY AND LEADERSHIP ON ORGANISATIONAL INTEGRITY IN PAKISTANI INDUSTRIAL SECTOR

2020 ◽  
Vol 8 (3) ◽  
pp. 1350-1362
Author(s):  
Muhammad Arif ◽  
Panteha Farmanesh
Keyword(s):  
Structural Equation ◽  
Quantitative Research ◽  
Gender Diversity ◽  
Industrial Sector ◽  
Equation Model ◽  
Work Place ◽  
Research Approach ◽  
The Difference ◽  
Meta Regression Analysis ◽  
The Impact

Purpose of the study: The main purpose of this study is to analyse the impact of gender diversity on organisational integrity in the context of Pakistani industrial sector. This study also investigates about the influences of female leaders on the association between diversity and organisational integrity and evaluates the effect of work place diversity on increase in organisational performance. Methodology: This study involves mediating and moderating variables along with independent and dependent variables, therefore researcher in this study has utilised Structural equation model (SEM) and Meta Regression Analysis (MRA) for achieving the main objectives of this research. The researcher has followed the positivism research philosophy as well as deductive research approach. In this study, researcher has followed quantitative research design to attain the key objectives of this study. Main Findings: From the results of study, it can be suggested that employers in Pakistan should diversify their workforce and also look to hire female candidates for the same position as male candidates since it would increase the work efficiency and integrity within an organisation as women tend to work more or equally passionately in their respective fields similar to men. Applications of this study: So, the study of impact of gender diversity on organisational integrity in the context of Pakistani industrial sector is not only useful for IT department but also useful for all organisational where gender diversity exists. Novelty/Originality of this study: Finally, it is important to clarify that one of the research gap that has been identified is the difference in wages between the male and the female employees. The difference in the pay scale between the two genders is considered to be a sophisticated gap that the research can deliberately overcome.

scholarly journals Mediating effect of job satisfaction in the relationship between leisure satisfaction and organization commitment according to individual versus group leisure activity of the employees

2012 ◽  
Vol 25 (1) ◽  
pp. 171-193 ◽  
Author(s):  
Sara Lim ◽  
SeaYoung Park
Keyword(s):  
Job Satisfaction ◽  
Structural Equation ◽  
Leisure Activity ◽  
Equation Model ◽  
Mediating Effect ◽  
Leisure Satisfaction ◽  
Organization Commitment ◽  
The Difference ◽  
Relationship Of ◽  
The Relationship

The purpose of this study was to examine the difference in leisure satisfaction, job satisfaction and organization commitment according to individual vs group leisure activity and to find out whether job satisfaction mediate relationship of leisure satisfaction and organization commitment. Participants of this study were 553 employees of various organizations in Jeonbuk. Reliability Cronbach's of questionnaire was .936～.846 and validity was verified by applying confirmatory factor analysis. The collected data were statistically analyzed through t-test, correlational analysis and Structural Equation Model(SEM) with SPSS 19.0 and AMOS 19.0. As a result, we found that there were significant differences between individual and group leisure activity on leisure satisfaction, job satisfaction and organization commitment. so the employees who participated in group leisure activity is higher than employees who participated in individual leisure activity. Also, job satisfaction fully mediated the relationship between leisure satisfaction and organization commitment both employees who participated in individual and group leisure activity. In other words, we confirmed that participating in group leisure activity raised the level of leisure satisfaction, and leisure satisfaction effected on job satisfaction and organization commitment. Finally, we discussed significance, limitation of this study then implications for further research.

scholarly journals Which Cognitive Abilities Make the Difference? Predicting Academic Achievements in Advanced STEM Studies

2018 ◽  
Vol 6 (4) ◽  
pp. 48 ◽  
Author(s):  
Michal Berkowitz ◽  
Elsbeth Stern
Keyword(s):  
Spatial Ability ◽  
Stem Education ◽  
Undergraduate Students ◽  
Cognitive Abilities ◽  
Structural Equation ◽  
Equation Model ◽  
Stem Learning ◽  
Ability Test ◽  
Reasoning Abilities ◽  
The Difference

Previous research has shown that psychometrically assessed cognitive abilities are predictive of achievements in science, technology, engineering and mathematics (STEM) even in highly selected samples. Spatial ability, in particular, has been found to be crucial for success in STEM, though its role relative to other abilities has been shown mostly when assessed years before entering higher STEM education. Furthermore, the role of spatial ability for mathematics in higher STEM education has been markedly understudied, although math is central across STEM domains. We investigated whether ability differences among students who entered higher STEM education were predictive of achievements during the first undergraduate year. We assessed 317 undergraduate students in Switzerland (150 from mechanical engineering and 167 from math-physics) on multiple measures of spatial, verbal and numerical abilities. In a structural equation model, we estimated the effects of latent ability factors on students’ achievements on a range of first year courses. Although ability-test scores were mostly at the upper scale range, differential effects on achievements were found: spatial ability accounted for achievements in an engineering design course beyond numerical, verbal and general reasoning abilities, but not for math and physics achievements. Math and physics achievements were best predicted by numerical, verbal and general reasoning abilities. Broadly, the results provide evidence for the predictive power of individual differences in cognitive abilities even within highly competent groups. More specifically, the results suggest that spatial ability’s role in advanced STEM learning, at least in math-intensive subjects, is less critical than numerical and verbal reasoning abilities.

scholarly journals OER impact study perceived by faculty within ODL framework

2016 ◽  
Vol 11 (1) ◽  
pp. 78-89 ◽  
Author(s):  
Maximus Gorky Sembiring
Keyword(s):  
Student Learning ◽  
Structural Equation ◽  
Teaching Practice ◽  
Equation Model ◽  
Open Educational Resources ◽  
Productivity Improvement ◽  
Content Type ◽  
Significance Level ◽  
Satisfaction Index ◽  
The Difference

Purpose The purpose of this paper is, first, to scrutinize the determinants of key benefits of open educational resources (OER) to faculty. Second, it is to expose how, in which routines the variables involved, are interrelated. Design/methodology/approach An exploratory design is used in this study. Qualitatively, key benefits include integration, opportunity, efficiency, enrichment, and collaboration. These benefits have direct impacts on enhancing student learning, augmenting teaching practice, improving productivity, catalyzing changes in teaching practice, and supporting non-traditional learners. Quantitatively, the key benefit is moderating the variables. Integration, opportunity, efficiency, enrichment, and collaboration are independent variables. Variables like enhancing student learning, enriching teaching practice, improving productivity, catalyzing changes, and supporting non-traditional learners are the dependent variables. The study population comprised the 721 Universitas Terbuka (UT) faculty members. The respondents were chosen randomly by distributing 450 questionnaires. Only 203 questionnaires were completed. Importance performance analysis and customer satisfaction index (IPA-CSI) were used to measure the importance level of variables involved and their benefits. Structural equation model (SEM) was used to examine the ten hypotheses developed so that the author could understand the significance level and relations power among variables engaged with reference to the qualitative outcomes previously obtained. Findings Six hypotheses were validated by the analysis. Statistically, efficiency and integration affect key benefits. Likewise, moderating variables affect teaching practice enhancement, productivity improvement, catalyzing changes, and supporting non-traditional learners. Conversely, key benefits were neither interrelated by opportunity, enrichment, and collaboration nor learning enhancement. Practical implications This study highlighted that adoption, integration, and implementation of OER in the UT milieu do take place. Originality/value This study recognized the variation of qualitative vs quantitative outcomes. An auxiliary inquiry is needed with broader perspective by increasing the respondents sample in order to minimize the difference between qualitative and quantitative results.

scholarly journals Level Of ICT Usage and Perceived Attributes among Academicians

2017 ◽  
Vol 2 (2) ◽  
pp. 37
Author(s):  
Marlita Mat Yusof ◽  
Nurhazirah Hashim ◽  
Siti Noraini Mohd Tobi
Keyword(s):  
Structural Equation ◽  
Publishing House ◽  
Equation Model ◽  
Information Communication ◽  
Public And Private ◽  
The Public ◽  
International Publishing ◽  
The Difference ◽  
Public And Private Sector ◽  
Higher Institutions

This study applies Structural Equation Model for ICT usage in Higher Education (Usluel, Askar & Bass 2008) attempts to identify the level of ICT usage among academicians in UiTM and UNISEL, two higher institutions representing the public and private sector respectively. Subsequently, the relationship between the perceived attributes and the level of ICT usage among academicians is presented. This paper compares the difference and the most influential attributes of the aforementioned between the public and private learning institution. This paper concludes that there is a significant relationship between perceived attributes and the level of ICT usage among UITM and UNISEL academicians. However, UiTM registers compatibility whilst UNISEL records observability as their most influential perceived attribute that leads to the level of ICT usage. The findings of this research were made through questionnaire distributed to academicians from both institutions and the analysis was carried out to verify the hypotheses. Keywords: Level of Usage, Information Communication and Technology (ICT), Perceived Attributes, Academician © 2017 The Authors. Published for AMER ABRA by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.

scholarly journals The Impact of the Physical Attractiveness and Intellectual Competence on Loyalty

2020 ◽  
Vol 12 (10) ◽  
pp. 3970
Author(s):  
Wen-Chih Yeh ◽  
Chun-Chang Lee ◽  
Cheng Yu ◽  
Pei-Shan Wu ◽  
Jia-Yu Chang ◽  
...  
Keyword(s):  
Real Estate ◽  
Customer Loyalty ◽  
Physical Attractiveness ◽  
Structural Equation ◽  
Past Research ◽  
Equation Model ◽  
The Past ◽  
The Difference ◽  
The Impact ◽  
The Relationship

This study aims to explore the factors determining consumer loyalty to real estate agents. Based on the past literature regarding the factors of loyalty, the study considers physical attractiveness and intellectual competence combined with a traditional loyalty model in proposing its conceptual framework. It then estimates the relevant parameters using a linear structural equation model (SEM). The subjects of the study consist of consumers in Kaohsiung City, Taiwan, aged at least 20 years old who have experience in engaging the services of real estate companies during housing transactions. A total of 300 questionnaires were distributed, with 268 valid ones being returned, for a valid return rate of 89.33%. According to the empirical results, physical attractiveness indirectly influences satisfaction through trust and intellectual competence, with satisfaction in turn affecting customer loyalty. The effect of physical attractiveness on satisfaction through trust is more significant than its effect on satisfaction through intellectual competence. These findings show that the relationship among physical attractiveness, intellectual competence, and trust plays an important role in determining satisfaction and loyalty. Past studies related to loyalty introduced various factors of loyalty; however, they rarely explored the effects of physical attractiveness and intellectual competence on loyalty. That is the difference between this study and past research.

scholarly journals Score-Guided Structural Equation Model Trees

2021 ◽  
Vol 11 ◽  
Author(s):  
Manuel Arnold ◽  
Manuel C. Voelkle ◽  
Andreas M. Brandmaier
Keyword(s):  
Likelihood Ratio ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Likelihood Function ◽  
Past Research ◽  
Equation Model ◽  
Likelihood Ratios ◽  
Data Set ◽  
Tree Structures ◽  
Original Algorithm

Structural equation model (SEM) trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. In past research, SEM trees have been estimated predominantly with the R package semtree. The original algorithm in the semtree package selects split variables among covariates by calculating a likelihood ratio for each possible split of each covariate. Obtaining these likelihood ratios is computationally demanding. As a remedy, we propose to guide the construction of SEM trees by a family of score-based tests that have recently been popularized in psychometrics (Merkle and Zeileis, 2013; Merkle et al., 2014). These score-based tests monitor fluctuations in case-wise derivatives of the likelihood function to detect parameter differences between groups. Compared to the likelihood-ratio approach, score-based tests are computationally efficient because they do not require refitting the model for every possible split. In this paper, we introduce score-guided SEM trees, implement them in semtree, and evaluate their performance by means of a Monte Carlo simulation.

scholarly journals Score-Guided Structural Equation Model Trees

2020 ◽  
Author(s):  
Manuel Arnold ◽  
Manuel Voelkle ◽  
Andreas Markus Brandmaier
Keyword(s):  
Likelihood Ratio ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Statistical Power ◽  
Equation Model ◽  
Group Differences ◽  
Likelihood Ratios ◽  
Data Set ◽  
Tree Structures ◽  
Selection Of

Structural equation model (SEM) trees are data-driven tools for finding covariates that predict group differences in the parameters of an SEM. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. Currently, the selection of split variables among covariates involves the calculation of a likelihood ratio for each possible split of each covariate. Obtaining these likelihood ratios is computationally intensive. Moreover, comparing maximum likelihood ratios biases the selection process by favoring covariates with many different values. Several correction procedures for this selection bias have been proposed. Unfortunately, these procedures either reduce statistical power to detect group differences or impose an additional computational burden. As a remedy, we propose to guide the construction of SEM trees by a family of score-based tests instead of using likelihood ratios. These score-based tests monitor fluctuations in the case-wise derivatives of the likelihood function, also called scores, to detect parameter differences between groups. In contrast to the likelihood-ratio approach, score-based tests are computationally efficient because they do not require refitting the model for every possible split, they offer an unbiased selection of covariates, and have high statistical power. In this paper, we introduce score-guided SEM trees and its implementation in the R package semtree and evaluate their performance by means of a Monte Carlo simulation.

scholarly journals Sex-specific impact of diabetes mellitus on left ventricular systolic function and prognosis in heart failure

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Soongu Kwak ◽  
In-Chang Hwang ◽  
Jin Joo Park ◽  
Jae-Hyeong Park ◽  
Jun-Bean Park ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Heart Failure ◽  
Structural Equation ◽  
Systolic Function ◽  
Global Longitudinal Strain ◽  
Left Ventricular Systolic Function ◽  
Equation Model ◽  
Sem Analysis ◽  
Left Ventricular ◽  
The Difference

AbstractWe aimed to investigate the sex differences in associations of diabetes mellitus (DM) with echocardiographic phenotypes and clinical outcomes of heart failure (HF). We studied 4,180 patients admitted for acute HF between 2009 and 2016 (median follow-up, 31.7 months) whose left ventricular global longitudinal strain (LV-GLS) data were available. Patients were compared by sex and DM. Structural equation model (SEM) analysis was performed to evaluate the moderating effects of two causal paths, via ischemic heart disease (IHD) and LV-GLS, linking DM with mortality. Compared to non-diabetic women, diabetic women had significantly lower LV-GLS (11.3% versus 10.1%, p < 0.001), but the difference was attenuated within men (9.7% versus 9.2%, p = 0.014) (p-for-interaction by sex = 0.018). In Cox analyses, DM was an independent predictor for higher mortality in both sexes (women: adjusted hazard ratio [HR] 1.35, 95% confidence interval [CI] 1.15–1.59 versus men: HR 1.24, 95% CI 1.07–1.44, p-for-interaction by sex = 0.699). Restricted cubic spline curves showed that LV-GLS consistently declined, and mortality increased in women with worsening hyperglycemia, but these trends were not evident in men. In SEM analysis, the main driver from DM to mortality differed by sex; men had a stronger effect via IHD than LV-GLS, whereas LV-GLS was the only predominant path in women.

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