A Practical Example Comparing Principal Component Analysis and Principal Axis Factoring as Methods for the Identification of Latent Constructs - Softcover
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Seminar paper from the year 2011 in the subject Economics - Statistics and Methods, grade: 1,0, University of applied sciences, Munich, course: Research Methods, language: English, abstract: In this paper the historical and theoretical background of the factor analysis is briefly explained. Principal Component Analysis (PCA) and Principal Axis Factoring (PAF) are applied to a data set which has been generated in the scope of the evaluation of the implementation of Company X's corporate Strategy XX. The results clearly indicate that structural parts of the data collection instrument could be reproduced by the empirical data. The primary factors resulting from an orthogonal respectively oblique rotation are comparable but also show slight differences. Latent constructs like "Trust", "Job Satisfaction" "Disengagement" and "Pessimism" are indicated by the results. Secondary factors indicate a negative relationship between disengagement and leadership respectively transparency concerning the corporate strategy and job satisfaction. Also aspects of "state negativity" can be identified. This means that a general pessimistic attitude is related to a more pessimistic view on realized customer focus. The application of more elaborated methods would be needed to identify causal relationships.
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A Practical Example Comparing Principal Component Analysis and Principal Axis Factoring as Methods for the Identification of Latent Constructs
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Seminar paper from the year 2011 in the subject Economics - Statistics and Methods, grade: 1,0, University of applied sciences, Munich, course: Research Methods, language: English, abstract: In this paper the historical and theoretical background of the factor analysis is briefly explained. Principal Component Analysis (PCA) and Principal Axis Factoring (PAF) are applied to a data set which has been generated in the scope of the evaluation of the implementation of Company X's corporate Strategy XX. The results clearly indicate that structural parts of the data collection instrument could be reproduced by the empirical data.The primary factors resulting from an orthogonal respectively oblique rotation are comparable but also show slight differences. Latent constructs like 'Trust', 'Job Satisfaction' 'Disengagement' and 'Pessimism' are indicated by the results. Secondary factors indicate a negative relationship between disengagement and leadership respectively transparency concerning the corporate strategy and job satisfaction. Also aspects of 'state negativity' can be identified. This means that a general pessimistic attitude is related to a more pessimistic view on realized customer focus. The application of more elaborated methods would be needed to identify causal relationships. 32 pp. Englisch. Bestandsnummer des Verkäufers 9783656923695
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Seminar paper from the year 2011 in the subject Economics - Statistics and Methods, grade: 1,0, University of applied sciences, Munich, course: Research Methods, language: English, abstract: In this paper the historical and theoretical background of the factor analysis is briefly explained. Principal Component Analysis (PCA) and Principal Axis Factoring (PAF) are applied to a data set which has been generated in the scope of the evaluation of the implementation of Company X's corporate Strategy XX. The results clearly indicate that structural parts of the data collection instrument could be reproduced by the empirical data.The primary factors resulting from an orthogonal respectively oblique rotation are comparable but also show slight differences. Latent constructs like 'Trust', 'Job Satisfaction' 'Disengagement' and 'Pessimism' are indicated by the results. Secondary factors indicate a negative relationship between disengagement and leadership respectively transparency concerning the corporate strategy and job satisfaction. Also aspects of 'state negativity' can be identified. This means that a general pessimistic attitude is related to a more pessimistic view on realized customer focus. The application of more elaborated methods would be needed to identify causal relationships. Bestandsnummer des Verkäufers 9783656923695
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Taschenbuch. Zustand: Neu. A Practical Example Comparing Principal Component Analysis and Principal Axis Factoring as Methods for the Identification of Latent Constructs | Holger Bodenmüller | Taschenbuch | 32 S. | Englisch | 2015 | GRIN Verlag | EAN 9783656923695 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu. Bestandsnummer des Verkäufers 104799328
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