VARIABILITY ANALYSIS OF REGIONAL INDICATORS OF KAZAKHSTAN’S REAL SECTOR OF ECONOMY

The study’s main purpose is to analyze the variability of regional indicators of Kazakhstan’s real sector of economy by leveraging Factor Analysis. Processed indicators encompass 1999–2019, i.e. 21 years. The number of regions is 14. Input information was compressed as follows: mean values of indicators of each region in 21 years were calculated and then one final table was created. Results of Factor Analysis. All industries of real sector of economy may be lined up in four groups according to common interregional variability criterion: 1) mining industry; 2) manufacturing industry; 3) agriculture (crop and livestock breeding); 4) transport and communication. According to Factor Analysis methodology, it is considered that there is a certain factor behind the indicators of each selected group, i.e. there is an objective reason. The factors are independent, therefore, the indicators of different groups do not have statistical relations among each other. The indicators of mining and manufacturing industries have certain regional orientations, i.e. few areas have either mining or manufacturing sectors developed. Agriculture is also a region-dependent sector of the real economy. Significant part of regional variability of livestock sector and almost total interregional variability of population have common factor behind (total variances 0.57 and 0.94). In other words, livestock breeding is predominantly developed in regions with a denser population. Transport and communication sectors are not bound to certain regions, they flourish in heavily populated areas (total variances 0.69; 0.85; 0.61). Interregional fluctuations of resource indicator, i.e. capital investments, almost totally match with similar fluctuations in mining and construction (total variances 0.94; 0.70; 0.97). As for capital investments directed to other sectors, their interregional variability is negligible. What is this talking about? Capital investments, except for mining and construction, are pinpoint investments, i.e. allocated to certain regions only.

Download Full-text

Spectrum Decomposition through Maximum Likelihood Common Factor Analysis of the EPR Spectra of Na+ Containing Carbonated Apatites Dried at 400°C

Calcified Tissue International ◽

10.1007/bf03549785 ◽

1993 ◽

Vol 53 (6) ◽

pp. 416-423

Author(s):

Peter D. W. Moens ◽

Ronald M. H. Verbeeck ◽

Paul J. De Volder ◽

Freddy J. Callens ◽

Erna A. P. De Maeyer

Keyword(s):

Factor Analysis ◽

Maximum Likelihood ◽

Common Factor ◽

Epr Spectra ◽

Common Factor Analysis ◽

Carbonated Apatites ◽

Spectrum Decomposition

Download Full-text

Internal consistency and factor structure of Jenkins Sleep Scale: cross-sectional cohort study among 80 000 adults

BMJ Open ◽

10.1136/bmjopen-2020-043276 ◽

2021 ◽

Vol 11 (1) ◽

pp. e043276

Author(s):

Juhani Juhola ◽

J P A Arokoski ◽

Jenni Ervasti ◽

Mika Kivimäki ◽

Jussi Vahtera ◽

...

Keyword(s):

Factor Analysis ◽

Cohort Study ◽

Internal Consistency ◽

Common Factor ◽

Secondary Outcome ◽

Cross Sectional ◽

Healthy Working ◽

Confirmatory Factor ◽

Working Age ◽

Working Age Population

ObjectivesTo assess the internal consistency and construct validity of the Finnish translation of the Jenkins Sleep Scale (JSS) in a large healthy working-age population with diverse work characteristics.DesignSurvey-based cross-sectional cohort study.SettingSurvey conducted by an institute of occupational health.ParticipantsEmployees of 10 towns and 6 hospital districts.Primary and secondary outcome measuresThe internal consistency defined by a Cronbach’s alpha. Exploratory and confirmatory factor analyses to evaluate the construct structure of the JSS.ResultsOf 81 136 respondents, 14 890 (18%) were men and 66 246 (82%) were women. Their average age was 52.1 (13.2) years. Of the respondents, 41 823 (52%) were sleeping 7 or less hours per night. The mean JSS total score was 6.4 (4.8) points. The JSS demonstrated high internal consistency with an alpha of 0.80 (lower 95% confidence limit 0.80). Exploratory factor analysis supported a one-factor solution with eigenvalue of 1.94. Confirmatory factor analysis showed that all four items were positively correlated with a single common factor explaining 44%–61% of common factor’s variance.ConclusionsThe Finnish translation of JSS was found to be a unidimensional scale with good internal consistency. As such, the scale may be recommended as a practicable questionnaire when studying sleep difficulties in a healthy working-age population.

Download Full-text

Blurring the Distinctions Between Component Analysis and Common Factor Analysis

Multivariate Behavioral Research ◽

10.1207/s15327906mbr2501_6 ◽

1990 ◽

Vol 25 (1) ◽

pp. 53-59 ◽

Cited By ~ 41

Author(s):

Stanley A. Mulaik

Keyword(s):

Factor Analysis ◽

Common Factor ◽

Component Analysis ◽

Common Factor Analysis

Download Full-text

Dimensions of Jewish-American Identity

Psychological Reports ◽

10.2466/pr0.1973.33.3.891 ◽

1973 ◽

Vol 33 (3) ◽

pp. 891-900 ◽

Cited By ~ 45

Author(s):

Itai Zak

Keyword(s):

United States ◽

Factor Analysis ◽

Test Scores ◽

Common Factor ◽

The United States ◽

American Identity ◽

Jewish American ◽

Cast Doubt ◽

The Common ◽

High Degree

The main problem posed in this study is: What are the content and structure of Jewish and American identity? The Jewish-American Identity Scale, which was adapted and refined for this study, was administered in 1971 to four samples, totaling 1006 Jewish-American college students from various parts of the United States. Initially, factor analysis was applied to the separate samples. Intersample comparisons of factor structures indicated a high degree of congruency; consequently, the samples were combined for subsequent analyses. Factor analysis of the test scores demonstrated that most of the common factor variance was appropriated by two relatively orthogonal factors. Items dealing with American identity and those dealing with Jewish identity had medium to high loadings on the two respective factors. These findings supported the hypothesis of the duality and the orthogonality of dimensions of Jewish and American identity, and cast doubt on the notion forwarded by some researchers that Jewish-American identity forms a bipolar continuum.

Download Full-text

Scale development of occupational identity and testing model of antecedents and outcome variables of occupational identity

The Korean Journal of Industrial and Organizational Psychology ◽

10.24230/kjiop.v27i4.617-642 ◽

2014 ◽

Vol 27 (4) ◽

pp. 617-642 ◽

Cited By ~ 2

Author(s):

HongJoon Yoo ◽

TaeYong Yoo ◽

TaeIn Chung ◽

Seongho Bae ◽

AReum Jo

Keyword(s):

Factor Analysis ◽

Factor Structure ◽

Discriminant Validity ◽

Common Factor ◽

Occupational Identity ◽

Future Research ◽

Workplace Satisfaction ◽

Confirmatory Factor ◽

Intention To Continue ◽

Three Factor

The first purpose of this study was to define the construct of occupational identity and develop the scale of occupational identity, the second purpose of this study was to examine the factor structure of occupational identity using exploratory common factor analysis and test the discriminant validity of occupational identity with workplace satisfaction, and third purpose of this study was to test the model of antecedents and outcome variables of occupational identity using confirmatory factor analysis. For fulfilling these purposes, three studies were conducted. Data were gathered from 390 workers in study 1, 505 workers in study 2, 1,115 workers in study 3. As a result, the three-factor structure of occupational identity was stably replicated, although the sample was changed. The occupational identity had discriminant validity with workplace satisfaction. Except for person-occupation fit(a subfactor of occupational identity) had a high correlation with general, occupational satisfaction(a subfactor of workplace satisfaction), other subfactors of occupational identity generally had low correlations with other subfactors of workplace satisfaction. It was found that the occupational identity was derived from occupational reputation, dedication to the occupation, occupational pride, and mission to the occupation. And the occupational identity resulted in the purpose of the worker’s life and intention to continue the worker’s occupation. Based on these results, We made discussions about implications, limitations, and future research tasks.

Download Full-text

A valid and reliable measure of nothing: disentangling the “Gavagai effect” in survey data

PeerJ ◽

10.7717/peerj.10209 ◽

2020 ◽

Vol 8 ◽

pp. e10209

Author(s):

Victor B. Arias ◽

Fernando P. Ponce ◽

Martin Bruggeman ◽

Noelia Flores ◽

Cristina Jenaro

Keyword(s):

Factor Analysis ◽

Psychometric Properties ◽

Common Factor ◽

Response Styles ◽

Sufficient Evidence ◽

Actual Structure ◽

Factorial Model ◽

Suitable Structure ◽

High Internal Consistency ◽

Central Term

Background In three recent studies, Maul demonstrated that sets of nonsense items can acquire excellent psychometric properties. Our aim was to find out why responses to nonsense items acquire a well-defined structure and high internal consistency. Method We designed two studies. In the first study, 610 participants responded to eight items where the central term (intelligence) was replaced by the term “gavagai”. In the second study, 548 participants responded to seven items whose content was totally invented. We asked the participants if they gave any meaning to “gavagai”, and conducted analyses aimed at uncovering the most suitable structure for modeling responses to meaningless items. Results In the first study, 81.3% of the sample gave “gavagai” meaning, while 18.7% showed they had given it no interpretation. The factorial structures of the two groups were very different from each other. In the second study, the factorial model fitted almost perfectly. However, further analysis revealed that the structure of the data was not continuous but categorical with three unordered classes very similar to midpoint, disacquiescent, and random response styles. Discussion Apparently good psychometric properties on meaningless scales may be due to (a) respondents actually giving an interpretation to the item and responding according to that interpretation, or (b) a false positive because the statistical fit of the factorial model is not sensitive to cases where the actual structure of the data does not come from a common factor. In conclusion, the problem is not in factor analysis, but in the ability of the researcher to elaborate substantive hypotheses about the structure of the data, to employ analytical procedures congruent with those hypotheses, and to understand that a good fit in factor analysis does not have a univocal interpretation and is not sufficient evidence of either validity nor good psychometric properties.

Download Full-text

Intercorporate default contagion from industry failures: Stress testing on creditee linkage networks of China

Journal of Financial Engineering ◽

10.1142/s2345768614500196 ◽

2014 ◽

Vol 01 (02) ◽

pp. 1450019 ◽

Cited By ~ 2

Author(s):

Mingmin Yang ◽

Haoyu Gao ◽

Zhigang Cao ◽

Xiaoguang Yang

Keyword(s):

Manufacturing Industry ◽

Mining Industry ◽

Logistic Function ◽

Financial Contagion ◽

Underlying Network ◽

Initial Shock ◽

Bad Loans ◽

Default Contagion ◽

Regulatory Commission ◽

Two Parameter

This paper explores a simulation framework to examine the financial contagion on the creditee linkage networks, owing to a comprehensive loan-level database of China Banking Regulatory Commission (CBRC). We merge two kinds of connections together, i.e., loan guarantee and shareholding relationships, when constructing our underlying network. Default transmission probabilities are characterized by the two-parameter logistic function with a variant of leverage. Our main finding is that, under the above channel, contagion spreads in a linear form. To be precise, as the scale of the initial shock grows, the total number of default firms and the amount of bad loans incurred both increase linearly. The main reason for this is that the underlying network is rather sparse. Within the same ratio of initially default companies, the Manufacturing Industry is likely to cause the largest number of companies to fail and the largest amount of bad loans. We also find that the default contagion mostly spreads within the same industries, explaining again why the domino effect is very limited. We investigate the impacts on different regions from industry failures, and get many interesting findings, e.g., most industries may influence the Yangtze Delta Economic Circle significantly except for Agriculture and the Mining Industry.

Download Full-text

Financial Quality Evaluation of Listed Companies Based on Factor Analysis Method

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.401-403.2247 ◽

2013 ◽

Vol 401-403 ◽

pp. 2247-2251

Author(s):

Zhi Hong Lin ◽

Ting Ting Guo

Keyword(s):

Factor Analysis ◽

Manufacturing Industry ◽

Comprehensive Evaluation ◽

Listed Companies ◽

Management Decision ◽

Analysis Method ◽

Electrical Machinery ◽

Financial Quality ◽

Financial Index ◽

Spss Software

Financial index of listed companies is the key to understanding and evaluating the company's financial quality. This article introduces the method of factor analysis in comprehensive evaluation of financial quality, uses SPSS software for a comprehensive evaluation of electrical machinery and equipment manufacturing industry 10 listed companies financial quality, in order to provide support for investors and managers to make investment decisions and management decision.

Download Full-text