TY - CHAP M1 - Book, Section TI - Regression with a Qualitative Dependent Variable: Logistic Regression A1 - Glantz, Stanton A. A1 - Slinker, Bryan K. A1 - Neilands, Torsten B. PY - 2017 T2 - Primer of Applied Regression and Analysis of Variance, 3e AB - All the statistical methods we have developed so far have been for quantitative dependent variables, measured on more-or-less continuous scales. The assumptions of linear regression—in particular, that the mean value of the population at any combination of the independent variables be a linear function of the independent variables and that the variation about the plane of means be normally distributed—required that the dependent variable be measured on a continuous scale. In contrast, because we did not need to make any assumptions about the nature of the independent variables, we could incorporate qualitative or categorical information (such as whether or not a Martian was exposed to secondhand tobacco smoke) into the independent variables of the regression model. There are, however, many times when we would like to evaluate the effects of multiple independent variables on a qualitative dependent variable, such as the presence or absence of a disease. Because the methods that we have developed so far depend strongly on the continuous nature of the dependent variable, we will have to develop a new approach to deal with the problem of regression with a qualitative dependent variable. SN - PB - McGraw-Hill Education CY - New York, NY Y2 - 2024/03/29 UR - accessbiomedicalscience.mhmedical.com/content.aspx?aid=1141901984 ER -