2. Linear Regression

Practical Issues

  1. Bee Choo Tai1 and
  2. David Machin2

Published Online: 11 OCT 2013

DOI: 10.1002/9781118721957.ch2

Regression Methods for Medical Research

Regression Methods for Medical Research

How to Cite

Tai, B. C. and Machin, D. (2013) Linear Regression, in Regression Methods for Medical Research, John Wiley & Sons Ltd, Oxford. doi: 10.1002/9781118721957.ch2

Author Information

  1. 1

    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System; Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore

  2. 2

    Medical Statistics Unit, School of Health and Related Sciences, University of Sheffield; Cancer Studies, Faculty of Medicine, University of Leicester, Leicester, UK

Publication History

  1. Published Online: 11 OCT 2013
  2. Published Print: 29 NOV 2013

ISBN Information

Print ISBN: 9781444331448

Online ISBN: 9781118721957

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Keywords:

  • discrete covariates;
  • linear regression models;
  • study design;
  • unordered categorical covariate

Summary

This chapter describes the different types of covariates that may arise when using linear regression models and how preliminary screening of these using graphical techniques may be useful. It describes how an unordered categorical covariate of more than two levels is included in a model by the technique of creating dummy variables. The authors include discussion of covariates of ordered categorical and numerically discrete forms. Several methods are described for verifying whether or not a chosen linear model, once fitted to the data, is appropriate for the study concerned. The authors caution against the use of ‘in-house’ statistical software and recommend that as simple a model structure as possible is used for summarizing the data collected. Aspects concerned with the choice of study design and subsequent reporting are also included.