Interpretation of multivariate models requires knowing how much the fit of the model is impaired by changes in the parameters. The relation of parameter change to loss of goodness of fit can be called parameter sensitivity. Formulas are presented for assessing the sensitivity of multiple regression and principal component weights. (Author/JKS)

The misleading character of the correlation coefficient was investigated in two studies of intuitive statistical behavior: subjective estimation of partial correlation and subjective estimation of the minimum possible correlation between two variables given their equal correlation with a third. (Author/JKS)

Systematic procedures are outlined for testing the assumption made on the dependent variables in a variety of statistical techniques. Specifically, procedures are outlined for testing the assumption that the dependent variables are measuring the same constructs in the same metrics with equivalent reliabilities across all subgroups. (Author/JKS)

Two major and two minor principles are shown to serve to generate a large number of multivariate models, including canonical analysis, factor analysis, and latent trait test theory. The statistical underpinnings of the theory are discussed. (Author/JKS)