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Henning Lohmann

In: The SAGE Handbook of Regression Analysis and Causal Inference

Chapter 6: Non-Linear and Non-Additive Effects in Linear Regression

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Non-Linear and Non-Additive Effects in Linear Regression
Non-linear and non-additive effects in linear regression
HenningLohmann
Introduction

This chapter discusses the approaches to modeling non-additive and non-linear relationships within the framework of multiple regression. When using multiple regression in its simplest form we have to assume that relationships are linear and additive (see Chapter 5 in this volume). Linearity means that the strength of a relationship between a variable X and a variable Y does not differ across the range of the variable X. However, many research questions in the social sciences address non-linear relationships. We speak of additivity if the relationship between a variable X1 and a variable Y is not dependent on the value of a variable X2. Yet often we observe interactions between two variables: the ...

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