AN INTRODUCTION TO LOGISTIC-REGRESSION WITH AN APPLICATION TO THE ANALYSIS OF LANGUAGE RECOVERY FOLLOWING A STROKE

The aim of a statistical model is to present a simplified representati on of the underlying structure in a data set by separating systematic features from random variation. Sometimes the purpose of a statistical model is to provide a simple descriptive summary of the data and some times it is to use the data for comparative or inferential purposes. I n practice, the specification of a statistical model requires a thorou gh understanding of the substantive area of application, an assessment of the validity of the assumptions of the model, and an evaluation of the fit of the model to the data. In this paper, as an illustration o f these aspects of the statistical modeling of data, we consider the s pecification, application, and interpretation of a logistic regression model for the investigation of relationships between binary response data and a collection of explanatory variables. We illustrate applicat ions of the methodology using data from a prospective study of spontan eous language recovery following a stroke (Holland, Greenhouse, Fromm, and Swindell, 1989).