Factor analysis


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Factor analysis

A statistical procedure that seeks to explain a certain phenomenon, such as the return on a common stock, in terms of the behavior of a set of predictive factors.

Factor Analysis

The analysis of seemingly unrelated phenomena and their disparate and combined effect on an investment. Factor analysis takes a large number of dependent variables and seeks to isolate the independent variables determining them. Isolating the independent variables (called factors in this context) helps reduce the number of variables that the analyst must study in order to make accurate statements and predictions about the direction of an investment.
References in periodicals archive ?
Table-6: Model Fit Statistics of confirmatory factor analysis for Urdu Version of PANAS (N=495).
However, this could be partly solved by iterations of factor analysis that include the latest input data.
Rotation is a very esoteric topic in factor analysis and has a lot of subjective interpretations, but the authors have done a good job in demystifying this topic and providing a decision tree for rotating the factors which would be quite useful for the researchers.
Thus, LDA is a particular case of factor analysis framework when the entire weight matrix is 1 and the basis of partition is class information.
Exploratory factor analysis (EFA) is concerned with the question of how many factors are necessary to explain the relations among a set of indicators and with the estimation of the factor loadings, whereas confirmatory factor analysis (CFA) is concerned with parameter estimation and tests of hypotheses regarding, for example, the number of factors underlying the relations among a set of indicators (Pedhazur, Schmelkin 1991).
On the other hands, factor analysis is suitable multivariate technique in identify and determination of independent factors that are effective on plant traits separately.
Factor analysis in the development and refinement of clinical assessment instruments.
In our study we have used factor analysis for a specific purpose to identify the variables falling under two different factors representing the controls.
Use of Factor Analysis Scores in MLRA: The appropriateness of factor analysis was tested with Kaiser- Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity (Sharma, 1996).
A second order factor analysis yielded three dimensions.
Discriminant function analysis was carried out using the food and nutrient factor scores derived through the factor analysis to determine as to how correctly those people who were chronic energy-deficient or overweight/obese are classified.