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common factor analysis

How to Reduce the Number of Variables to Analyze

by Christos Giannoulis 1 Comment

by Christos Giannoulis

Many data sets contain well over a thousand variables. Such complexity, the speed of contemporary desktop computers, and the ease of use of statistical analysis packages can encourage ill-directed analysis.

It is easy to generate a vast array of poor ‘results’ by throwing everything into your software and waiting to see what turns up. [Read more…] about How to Reduce the Number of Variables to Analyze

Tagged With: common factor analysis, dependent variable, Factor Analysis, independent variable

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Four Common Misconceptions in Exploratory Factor Analysis

by guest contributer Leave a Comment

by Christos Giannoulis, PhD

Today, I would like to briefly describe four misconceptions that I feel are commonly perceived by novice researchers in Exploratory Factor Analysis:

Misconception 1: The choice between component and common factor extraction procedures is not so important.

In Principal Component Analysis, a set of variables is transformed into a smaller set of linear composites known as components. This method of analysis is essentially a method for data reduction.

[Read more…] about Four Common Misconceptions in Exploratory Factor Analysis

Tagged With: common factor analysis, communality, EFA, eigenvalue, Exploratory Factor Analysis, oblique rotation, orthogonal rotation, PCA, principal axis factor analysis, principal component analysis, rotation, sample size, simple structure

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