scholarly journals Drivers of Spatial Heterogeneity in the Russian Forest Sector: A Multiple Factor Analysis

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1635
Author(s):  
Roman V. Gordeev ◽  
Anton I. Pyzhev ◽  
Miron A. Yagolnitser
Keyword(s):  
Factor Analysis ◽  
Spatial Heterogeneity ◽  
Far East ◽  
Forest Sector ◽  
Negative Consequences ◽  
Multiple Factor Analysis ◽  
Foreign Markets ◽  
Investment Projects ◽  
Capital Development ◽  
Multiple Factor

This study explored the regional differences in the forest industry and management via a Multiple Factor Analysis approach. The dataset used comprises all Russian regions and 34 variables that comprehensively describe the situation in the sector. Based on the Multiple Factor Analysis, the variables contributing most to the spatial heterogeneity in Russian forestry were divided into industrial and forestry factors. The regions leading in the development of the timber industry are mainly located in the Northwestern and Southeastern parts of Russia. They show similarities in high logging volumes, investment attractiveness, and competitiveness in foreign markets. However, a divergence was found between the Northwestern regions and the Siberian and the Far East territories in terms of forest management factors. The Western part of Russia benefits from the density of the population and infrastructure, and proximity to the national financial centers and European markets. By comparison, Asian Russia suffers from labor shortages caused by negative demographic trends and the negative consequences of climate change, resulting in an increase in forest losses and a lack of control, finance, and transport accessibility due to the vast territory. To alleviate regional inequalities, we propose the introduction of private ownership of forests, support for investment projects, and human capital development.

scholarly journals Multiple factor analysis of eating patterns to detect groups at risk of malnutrition among home-dwelling older subjects in 2015

BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e023548
Author(s):  
Marc-Antoine Sanchez ◽  
Didier Armaingaud ◽  
Yasmine Messaoudi ◽  
Aude Letty ◽  
Rachid Mahmoudi ◽  
...  
Keyword(s):  
Older Adults ◽  
Factor Analysis ◽  
Food Intake ◽  
Dietary Habits ◽  
Eating Patterns ◽  
Multiple Factor Analysis ◽  
Older Subjects ◽  
Multiple Factor ◽  
Group 1 ◽  
Meal Delivery

ObjectiveWe aimed to describe eating patterns among home-dwelling older subjects to establish typologies of eaters at higher or lower risk of malnutrition.DesignCross-sectional study between June and September 2015 using a standardised questionnaire. The questionnaire was given to home-help employees (responsible for delivering meals to home-dwelling older persons and helping them to eat). The employees were asked to complete the questionnaire three times during the same week, for the same older adults, in order to identify the totality of their food intake.SettingRegistered customers of the home meal delivery company ‘Azaé’ (France).Participants605 older home-dwelling persons were randomly selected among customers served by the home meal delivery company.OutcomesMultiple factor analysis was used to understand the different modes of food consumption and to establish eating profiles. Hierarchical classification was performed to construct eating profiles corresponding to the dietary habits of the respondents.ResultsAverage age of the older adults was 85.3 years; 73.5% were women. Overall, 59% of participants reported that they ate out of habit, while 33.7% said they ate for pleasure. We identified four different groups of eaters, at varying levels of risk for malnutrition. Individuals in group 4 had the highest food intake in terms of quantity; and were less dependent than individuals in group 1 (p=0.05); group 1 was at highest risk of malnutrition.ConclusionImproved understanding of eating habits can help detect risky behaviours and help caregivers to promote better nutrition among home-dwelling older subjects.

scholarly journals The appropriateness of sum scores as estimates of factor scores in the multiple factor analysis of ordered-categorical responses.

2020 ◽  
Author(s):  
Pere Ferrando ◽  
Urbano Lorenzo-Seva
Keyword(s):  
Factor Analysis ◽  
Unit Weight ◽  
Factor Scores ◽  
Multiple Factor Analysis ◽  
Non Linear ◽  
Categorical Responses ◽  
Sum Scores ◽  
Biased Estimates ◽  
Ordered Categorical ◽  
Multiple Factor

<p>Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the non-linear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the practical relevance of these limitations is far from clear. In this article we adopt an empirical view, and propose indices and procedures (some of them new) for assessing the appropriateness of UWSSs in non-linear EFA applications. A new automated approach for obtaining UWSSs that maximize fidelity and correlational accuracy is proposed. The appropriateness of UWSSs under different conditions and the behavior of the present proposal in comparison with other more common approaches are assessed with a simulation study. A tutorial for interested practitioners is presented using an illustrative example based on a well-known personality questionnaire. All the procedures proposed in the article have been implemented in a well-known noncommercial EFA program. </p>

scholarly journals Recodificación de escalas en investigaciones sociológicas: una nueva metodología de validación. Aplicación a una encuesta política

2019 ◽  
Vol 77 (2) ◽  
pp. 130
Author(s):  
Elena Abascal ◽  
Vidal Díaz de Rada ◽  
Ignacio García Lautre ◽  
M. Isabel Landaluce
Keyword(s):  
Factor Analysis ◽  
Multiple Factor Analysis ◽  
Multiple Factor

La recodificación de variables es una etapa habitual en el análisis de datos de encuesta. No está exenta de riesgos, como pueden ser la introducción de sesgos o las posibles deformaciones de los datos originales. En este trabajo se propone una metodología de validación de cualquier recodificación, tanto de variables de escala métrica, como de escala categórica para reducir el número de categorías. El objetivo de la metodología propuesta es comprobar la adecuación de la recodificación, indicando en qué medida los datos recodificados mantienen la misma estructura de los datos originales. La metodología se basa en el uso de un método factorial, Multiple Factor Analysis (MFA), aplicado sobre una tabla global obtenida como yuxtaposición de los datos medidos con la escala original y los mismos datos medidos con la escala recodificada. El procedimiento ha sido testado a partir de un conjunto de datos reales extraídos de una encuesta de opinión pública sobre los principales políticos del Parlamento Español.

scholarly journals University performace through Multiple Factor Analysis

2019 ◽  
Author(s):  
Delimiro Alberto Visbal Cadavid ◽  
Mónica Martínez-Gómez ◽  
Rolando Escorcia-Caballero
Keyword(s):  
Higher Education ◽  
Factor Analysis ◽  
Higher Education Institutions ◽  
Public Higher Education ◽  
Multiple Factor Analysis ◽  
High Level ◽  
The University ◽  
High Degree ◽  
Multiple Factor ◽  
Year 2013

This work applies the Multiple Factor Analysis (MFA) as an exploratory methodology to analize the indicators of the education´s management that belong to 32 Colombian public Higher Education Institutions (HEIs) along the year 2013. The product of this work indicates that the majority of HEIs have similar structures, being different and better scored the following: La Universidad Nacional (UNAL), Antioquia (UDEA), Nacional Abierta y a Distancia (UNAD), Pamplona y del Valle. Also the UDEA has a high development in extension, formation, capacity and research which is considered one of the best HEIS in the country. The university of Valle has a high degree of welfare, formation and extension, besides moderate capacities on research in comparission with the UDEA wich is superior to the rest of the HEIs. Pamplona has too a high level of formation, extension and moderate weflare, research and capacity in relation to the UNAD. It worth to mention that UNAL is the best located on extension. However, it is surpassed by other University (UDEA) because has a better development in some variables associated to research and extension. To finish, there are other HEIs with too many weaknesses on the indicators of the education´s management wich are UFPS Ocaña, Sucre and Pacifico. These universities show certain problems of research, extension and capacity, but fundamentally strong shortcomings in formation and welfare.

scholarly journals The Appropriateness of Sum Scores as Estimates of Factor Scores in the Multiple Factor Analysis of Ordered-Categorical Responses

2020 ◽  
pp. 001316442093810
Author(s):  
Pere J. Ferrando ◽  
Urbano Lorenzo-Seva
Keyword(s):  
Factor Analysis ◽  
Unit Weight ◽  
Practical Relevance ◽  
Factor Scores ◽  
Multiple Factor Analysis ◽  
Categorical Responses ◽  
Sum Scores ◽  
Biased Estimates ◽  
Ordered Categorical ◽  
Multiple Factor

Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the nonlinear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the practical relevance of these limitations is far from clear. In this article, we adopt an empirical view and propose indices and procedures (some of them new) for assessing the appropriateness of UWSSs in nonlinear EFA applications. A new automated approach for obtaining UWSSs that maximize fidelity and correlational accuracy is proposed. The appropriateness of UWSSs under different conditions and the behavior of the present proposal in comparison with other more common approaches are assessed with a simulation study. A tutorial for interested practitioners is presented using an illustrative example based on a well-known personality questionnaire. All the procedures proposed in the article have been implemented in a well-known noncommercial EFA program.

Multiple-factor analysis.

2011 ◽  
pp. 248-278
Author(s):  
Charles C. Peters ◽  
Walter R. Van Voorhis
Keyword(s):  
Factor Analysis ◽  
Multiple Factor Analysis ◽  
Multiple Factor
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