Multivariable Model - Building: A Pragmatic Approach to Regression Anaylsis based on Fractional Polynomials for Modelling Continuous Variables

Patrick Royston · Willi Sauerbrei

Sep 2008 · Sold by John Wiley & Sons

About this ebook

Multivariable regression models are of fundamental importance in all areas of science in which empirical data must be analyzed. This book proposes a systematic approach to building such models based on standard principles of statistical modeling. The main emphasis is on the fractional polynomial method for modeling the influence of continuous variables in a multivariable context, a topic for which there is no standard approach. Existing options range from very simple step functions to highly complex adaptive methods such as multivariate splines with many knots and penalisation. This new approach, developed in part by the authors over the last decade, is a compromise which promotes interpretable, comprehensible and transportable models.

Ratings and reviews

Multivariable Model - Building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables by Patrick Royston, and Willi Sauerbrei is a textbook appropriate for clinical trialist and researchers in biomedical science, who are engaged in a daily basis in building multivariable prognostic models. While a number of texts exist for these audiences, this textbook was written at a more accessible level for those without any advanced statistical knowledge. The book begins laying the groundwork for model building as well as underlying the importance of modeling the appropriate functional form of continuous variables in order to minimize any residual confounding. Moreover, the authors have impressive coverage of the different statistical methodologies available for evaluating the functional form of continuous variables, like fractional polynomials and restrictive cubic splines. The advantages and drawbacks for each of these methods are also provided. The authors make use of statistical software packages throughout to demonstrate many of statistical procedures it presents. STATA is the primary package used and many of the necessary commands are given for readers who wish to take advantage of software to assist them in analyzing data. In addition to STATA, the authors provided the ink for resources in SAS and R. For survival analysis, STATA is the primary package used with details given on how to implement the methods covered in the text. This is an amazing book! As a physician-epidemiologist, I strongly recommend it. If you want to excel in multivariable model building, you will not be disappointed.

About the author

Patrick Royston DSc, is a senior statistician and cancer clinical realist at the MRC Clinical Trials Unit, London, an honorary professor of statistics at University College London and a fellow of the Royal Statistical Society. he has authored many research papers in biostatistics, and has published over 150 articles in leading statistical journals. Patrick is an experienced statistical consultant, Stata programmer and software author.

Willi Sauerbrei PhD, is a senior statistician and professor in medical biometry at the IMBI, University Medical Center Freiburg. He has authored many research papers in biostatistics and has published over 100 articles in leading statistical and clinical journals. He worked for more than two decades as an academic biostatistician and has extensive experience of cancer research, with a particular concern for breast cancer.