penalty of model complexity

• Penalty of model complexity
  For a given set of data and variables, the goodness of fit of a more complex, highly parameterized model tends to be greater than for simpler models because of the loss of degrees of freedom of the complex model. Thus, a good model fit indicated by fit measures may result from 1) a correctly specified model that adequately represents the sample data or 2) a highly overparamerized model that accounts for the fit of the mdoel in the sample, regardless of whether there is a match between the specified model and the population covariance matrix (Hu&Benterl,1995).