Standard Errors, Correlations and Model Analysis

In recent years there has been a great increase in the computing power and user-friendliness of packages that may be used for statistical analysis. One effect of these developments has been to bring progressively more sophisticated models within the scope of supposedly routine analysis by people who may or may not be adequately trained in statistics. Often a major purpose of such analysis is to carry out parsimonious model selection to fit a set of data. The purpose of this paper is to illustrate the need for caution when interpreting standard errors and other diagnostics used to guide the selection process.