http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Should I use linear or logistic regression?
a case of using logistic regression to study why American states make different policy choices
Students are often taught about linear regression, but not logistic regression. Regression analysis is an important methodological tool when investigating complex phenomenon where multiple independent variables might influence changes in the dependent variable. Linear regression is helpful in econometrics and other studies where the dependent variables tend to be continuous like money, but what about disciplines such as psychology and political science where the phenomenon studied are often dichotomous, yes/no type, variables such as did the respondent vote or not in the last election? For these studies, the researcher must use logistic regression. This case study explores the differences between linear and logistic regression through a discussion of a research project on why different American states made different policy choices. This research project focused on whether the states made certain welfare policy choices or not, so the dependent variable was dichotomous and called for a logistic regression analysis.
Includes bibliographical references and index.