ABSTRACT
This chapter is an overview of advanced statistical topics that an experimenter may want to use in the pursuit of finding the appropriate model for understanding and predicting specific outcomes. Because the topics are very complex and the techniques very tedious, the chapter will focus on explaining some of the idiosyncrasies and identifying some of the tests. However, it is assumed that computer software will be used, and therefore no critical tables are provided. (Readers who are interested in table values should consult any statistics book that deals with these topics.)
In attempting to choose an appropriate analytical technique, we sometimes encounter a problem that involves a categorical dependent variable and several metric (measurable) independent variables. For example, we may wish to distinguish good from bad credit risks. If we had a metric measure of credit risk, then we could use multivariate regression. But we may be able to ascertain only if someone is in the good or bad risk category, and this is not the metric type measure required by multivariate regression analysis.
