Fundamental to the factor analytic model is that some variables of theoretical interest cannot be directly observed; these unobserved variables are termed latent variables, or factors. Although latent variables cannot be directly observed, information related to them can be obtained indirectly by noting their effects on observed variables believed to represent them. The oldest and best-known statistical procedure for investigating relations between sets of observed and latent variables is that of factor analysis. In using this approach to data analyses, researchers examine the covariation among a set of observed variables in order to gather information on the latent constructs (or factors) that underlie them. Because factor analysis is concerned with the extent to which the observed variables are generated by the underlying latent constructs, strength ...

  • Loading...
locked icon

Sign in to access this content

Get a 30 day FREE TRIAL

  • Watch videos from a variety of sources bringing classroom topics to life
  • Read modern, diverse business cases
  • Explore hundreds of books and reference titles