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Ann Thorac Surg 2003;75:753-757
© 2003 The Society of Thoracic Surgeons

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The statistician’s page

Understanding logistic regression analysis in clinical reports: an introduction

^a The Virginia Mason Medical Center, Seattle, Washington, USA
^b Providence Health System, Portland, Oregon, USA

^* Address reprint requests to Dr Grunkemeier, St. Vincent Hospital and Medical Center, 9155 SW Barnes, Suite 33, Portland, OR 97225, USA
e-mail: ggrunkemeier@providence.org

The first 300 words of the full text of this article appear below.

Much of our understanding of biological effects and their determinants is gained through statistical regression analysis. Linear and nonlinear regression methods are often applied in the basic sciences. Clinical studies that evaluate the relative contribution of various factors to a single binary outcome, such as the presence or absence of death or disease, most often employ the method of logistic regression. The purpose of this article is to provide an introduction sufficient to permit clinicians who are unfamiliar with regression methodology to understand and interpret its results. We will begin by describing linear regression techniques in order to present basic concepts. We will then consider logistic regression at greater length because of its importance and increasing use by cardiothoracic surgeons.

The calculations involved in logistic regression are complex, but currently available personal computers and ubiquitous statistical software have brought the capability for performing the analysis to the desktop of virtually all clinicians. Consequently, one can hardly find a recent medical journal that does not include at least one report that employs this technique. Figure 1 illustrates the increasing use of logistic regression in studies appearing in three thoracic surgical journals during the last decade. After a description of logistic regression, we will present a clinical example illustrating the technique.

View larger version (42K): [in this window] [in a new window]   Fig 1. The percentage of papers appearing in three thoracic surgical journals, according to the year of publication. Numbers were obtained by searching the CTSNet Web site using the text string "logistic regression."

The term "regression" had its origin with the 19th century statistician Francis Galton. He used it to describe his observation that the sons of short fathers tended to be taller and sons of tall fathers shorter, so that the height of sons "regressed" to the mean height of all men. Galton’s friend Karl Pearson developed the mathematical basis for what . . . [Full Text of this Article]

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