The eigenvalue is a measure of how much of the variance of t...

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The eigenvalue is a measure of how much of the variance of theobserved...

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Dropping unimportant variables from your analysis Once you run a factor analysis and think you have some usable results its time to eliminate variables that are not strong enough They are usually the ones with low factor loadings factor loadings are explained in last although additional criteria should be considered before taking out a variable As a rule of thumb your variable should have a rotated factor loading of at least 04 meaning 4 or 4 onto one of the factors in order to be considered important Some researchers use much more stringent criteria such as a cutoff of 07 In some instances this may not be realistic for example when the highest loading a researcher finds in her analysis is 05 Other researchers relax the criteria to the point where they include variables with factor loadings of 02 Which cutoffs to use depends on whether you are running a confirmatory or exploratory factor analysis and on what is usually considered an acceptable cutoff in your field In addition a variable should ideally only load cleanly onto one factor Factor Loading The relationship of each variable to the underlying factor is expressed by the socalled factor loading Here is an example of the output of a simple factor analysis looking at indicators of wealth with just six variables and two resulting factors Variables Factor 1 Factor 2 Income 065 011 Education 059 025 Occupation 048 019 House value 038 060 Number of public parks in neighborhood 013 057 Number of violent crimes per year in neighborhood 023 055 The variable ....

The eigenvalue is a measure of how much of the variance of the observed variables a...

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