Three different discriminant techniques are applied and compared to analyze a complex data set of credit risks. A large sample is split into a training, a validation, and a test sample. The dependent variable is whether a loan is paid back without problems or not. Predictor variables are sex,...

Bielby (1986) argues that conventional practices for normalizing latent variable models can lead the applied researcher astray. He presents two examples to show how this may occur. In the first example, he considers the regression of income on education. In the second, he considers a panel model...

When using panel data important problems are often conveniently overlooked. These include model misspecification, asymptotic stability, unequally spaced panel waves, and the use of ordinal rather than metric data. While panel data may be useful to eliminate specification error, if the process...