We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
Published online by Cambridge University Press: 05 June 2012
Overview
Logistic regression is conceptually analogous to linear regression in that a single dependent variable is predicted from either a single predictor (simple logistic regression) or multiple predictors (multiple logistic regression) based on a prediction model. It is also permissible to use both quantitatively measured and dichotomously (binary) coded variables as predictors. Our example for this chapter involves a single quantitatively measured predictor variable.
Some differences between linear and logistic regression
Although the two regression methods are conceptually similar, the differences between linear and logistic regression are important. Three of the most salient differences are as follows:
In linear regression, the dependent variable is quantitatively measured; in logistic regression, the dependent variable is categorical. We will limit ourselves to a dichotomously coded dependent variable.
In linear regression, a straight line function is fitted to the data set by using an ordinary least squares method; in logistic regression, a logistic function (an S-shaped function) is fitted to the data set by using a maximum likelihood estimation procedure.
In linear regression the value of the quantitatively measured dependent variable is predicted; in logistic regression the dependent variable is categorical and what is predicted is the likelihood that a case with a certain value or values on the predictor(s) is a member of a particular group (the reference group).
To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Find out more about the Kindle Personal Document Service.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.
