Details

1 Models, tests and data. <p>2 Multiple linear regression.</p> <p>3 Logistic regression.</p> <p>4 Survival analysis.</p> <p>5 Random effects models.</p> <p>6 Other models.</p> <p>.</p> <p>Appendix 1: Exponentials and logarithms.</p> <p>Appendix 2: Maximum likelihood and significance tests.</p> <p>Appendix 3: Bootstrapping and variance robust standard errors.</p> <p>Appendix 4: Bayesian methods.</p> <p>Answers to exercises.</p> <p>Glossary.</p> <p>Index</p>

<b>From a review of the previous edition<br /> </b>“This closely written but readable presentation of advanced methods increasingly used in the medical literature uses clinical examples to give meaning to these statistical methods. The experienced author reports the essence of statistical methods with only minimal use of mathematical notation. Underlying concepts are well described in the introductory chapter and in appendices, and the statistical references are excellent. Cautions on the misuse of methods abound. Useful guidance on presentation of methods and results appears in each chapter. Brief presentations of this quality are rare.”<br /> <p><i>Annals of Internal Medicine, December 2001</i><br /> </p> <p><b>About SS1 & SS2<br /> </b>"These two books are quite amazing. The depth and detail contained in these two tiny volumes is quite stunning. The way the two books have been written is succinct, and yet, does allow the student to understand the way the material is presented."<br /> </p> <p><i>Senior Lecturer, Tissue Viability Unit</i></p>

M J Campbell, Professor of Medical Statistics, University of Sheffield, UK

<b>Updated companion volume to the ever popular Statistics at Square One (SS1)</b> <br /> <p>Statistical methods used in medical literature are increasingly complex but software available to apply these methods is becoming easier to use. The result is that consumers of the literature now have to grasp sophisticated methods which may be inappropriately applied.<br /> </p> <p>This book covers the sophisticated statistical methods and goes beyond the basics of SS1. It reviews the most commonly used modern statistical methods and highlights common misunderstandings. It is easy to read, with annotated computer outputs and a minimum of formulas.<br /> </p> <p>It provides worked examples of methods such as multiple and logistical regression and each chapter concludes with exercises to reinforce learning.<br /> </p> <p>This is for all those who need to understand statistics in clinical research papers and apply them in their own research, such as junior doctors and general practitioners.</p>

<b>From a review of the previous edition<br /> </b>“This closely written but readable presentation of advanced methods increasingly used in the medical literature uses clinical examples to give meaning to these statistical methods. The experienced author reports the essence of statistical methods with only minimal use of mathematical notation. Underlying concepts are well described in the introductory chapter and in appendices, and the statistical references are excellent. Cautions on the misuse of methods abound. Useful guidance on presentation of methods and results appears in each chapter. Brief presentations of this quality are rare.”<br /> <p><i>Annals of Internal Medicine, December 2001</i><br /> </p> <p><b>About SS1 & SS2<br /> </b>"These two books are quite amazing. The depth and detail contained in these two tiny volumes is quite stunning. The way the two books have been written is succinct, and yet, does allow the student to understand the way the material is presented."<br /> </p> <p><i>Senior Lecturer, Tissue Viability Unit</i></p>

GB