can we have eigen value less than one in factor analysis
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Using eigenvalues > 1 is only one indication of how many factors to retain. Other reasons include the scree test, getting a reasonable proportion of variance explained and (most importantly) substantive sense.
That said, the rule came about because the average eigenvalue will be 1, so > 1 is "higher than average".
On your second question: Are you asking how to know how many factors (latent variables) to retain? Or are you asking about which observed variables to retain?
If the former, see above and see any book on factor analysis. If the latter, each factor is a linear combination of all the observed variables (althou
That said, the rule came about because the average eigenvalue will be 1, so > 1 is "higher than average".
On your second question: Are you asking how to know how many factors (latent variables) to retain? Or are you asking about which observed variables to retain?
If the former, see above and see any book on factor analysis. If the latter, each factor is a linear combination of all the observed variables (althou
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