Common Factor Analysis Versus Principal Component Analysis: Choice for Symptom Cluster Research
نویسندگان
چکیده
منابع مشابه
Common factor analysis versus principal component analysis: choice for symptom cluster research.
PURPOSE The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). METHODS Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences f...
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Common factor analysis (CFA) and principal component analysis (PCA) are widely used multivariate techniques. Using simulations, we compared CFA with PCA loadings for distortions of a perfect cluster configuration. Results showed that nonzero PCA loadings were higher and more stable than nonzero CFA loadings. Compared to CFA loadings, PCA loadings correlated weakly with the true factor loadings ...
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In this paper we compare and contrast the objectives of principal component analysis and exploratory factor analysis. This is done through consideration of nine examples. Basic theory is presented in appendices. As well as covering the standard material, we also describe a number of recent developments. As an alternative to factor analysis, it is pointed out that in some cases it may be useful ...
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Consider the situation where a researcher wants to determine the predictors for the fitness level (yes/no) to be assessed by treadmill by collecting the variables (Table I) of 50 subjects. Unfortunately the treadmill machine in the air-con room has broken down (the participants do not want to run in the hot sun!), and no assessment of fitness could be carried out. What could be done to analyse ...
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ژورنال
عنوان ژورنال: Asian Nursing Research
سال: 2008
ISSN: 1976-1317
DOI: 10.1016/s1976-1317(08)60025-0