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: 15 June 2023
Chapter 3 introduces readers to correlation and regression analysis. Methods of correlation answer the question concerning the portion of variance that two variables share. Regression uses, in most cases, metric dependent and metric or categorical independent variables. The OLS solution for the standard case of one predictor and one outcome variable is derived. Based on this derivation, characteristics of model parameters are explained. Real-world data examples are given for simple regression (one predictor and one outcome variable) and for multiple regression (multiple predictors and one outcome variable). In addition, this chapter describes GLM approaches to curvilinear regression (regression lines are curved rather than straight to approximate non-linear variable relations), to curvilinear regression of repeated observations, to symmetric regression (where the regression of Y on X results in the same solution as the regression of X on Y), to best subset and stepwise selection regression (which results in an optimal selection from multiple predictors), and the recently developed direction dependence analysis to evaluate hypotheses concerning the causal flow of a variable association
To save this book to your Kindle, first ensure [email protected] 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.
