Question

Factors derived from factor analysis may themselves be interrelated. When such factors are themselves factor analyzed, the resulting factors are called

Answer 1

Resulting factors are called Second-order factors

What is factor analysis?

• Factor analysis is a statistical approach for describing variability in seen, correlated variables in terms of a possibly smaller number of unobserved variables known as factors.
• It is possible, for example, that fluctuations in six known variables mostly reflect variations in two unseen (underlying) variables.
• Factor analysis looks for such joint fluctuations in response to latent variables that are not noticed.
• Factor analysis may be regarded of as a specific form of errors-in-variables models since the observed variables are described as linear combinations of the possible factors plus "error" terms.
• It may help to deal with data sets where there are large numbers of observed variables that are thought to reflect a smaller number of underlying/latent variables.
• It is one of the most commonly used inter-dependency techniques and is used when the relevant set of variables shows a systematic inter-dependence and the objective is to find out the latent factors that create a commonality.

To Learn more about factor analysis from the given link

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