title: Study Design and Statistical Analysis: A Practical Guide for Clinicians
author: Mitchell Katz
description: "...Include a wealth of practical advice and could serve as a valuable addition to the statistical training of doctors." <br />Robert W. Hayden, Journal of Biopharmaceutical Statistics<br /><br />"The book starts at the beginning of research itself, with advice on selecting a research question and comparisons of different study types and designs.... Biostatisticians might want to keep [Katz's] books on hand to lend to colleagues..." <br />Biometrics, March 2007<br /><br />"The book succeeds in providing a comprehensive overview of the nuts and bolts of clinical research in a concise, readable package. The author presents information in a style that is light and enjoyable to read, and he excels at explaining tedious topics with a generous amount of appropriate anecdotes." <br />American College of Physicians, 2007, Halcyon Skinner, PhD, MPH - University of Wisconsin School of Medicine Public Health<br /><br />"Succeeds in providing a comprehensive overview of the nuts and bolts of clinical research in a concise, readable package." <br />Annals of Internal Medicine<br /><br />"The exposition... is greatly enhanced by the author's choice of excellent examples demonstrating many of the methodologies, including relevant tables and figures, culled and referenced from the clinical literature... a useful introduction to a novice investigator, especially for those with little access to a biostatistician." <br />Charles L. Liss, Merck Research Labs for The American Statistician<br /><br />"This book is full of excellent practical advice. I would recommend this book to anyone who teaches statistics in the health sciences. They will find it most useful." <br />Daniel W. Byrne, Vanderbuilt University for Teaching Statistics in Health Sciences Newsletter
zlib_text: CHAPTER 8
  Pitfalls
  The crooks already know these tricks; honest men must learn them
  in self-defense.
  –Darrel Huﬀ (1954)
  8.1
  Introduction
  The results of a well-designed and executed clinical trial should be
  evident from a few summary statistics — but stopping at those sum-
  maries in a manuscript is rare. It is reasonable to want to see if more
  can be learned from a long, expensive eﬀort. The temptation to over-
  interpret secondary analyses can be irresistible. Although exploring
  data and analyzing diﬀerent endpoints do sometimes lead to new
  insights, far too often they lead to implausible hypotheses and faulty
  conclusions. In this chapter we discuss problems with some common
  types of analyses that have been used to try to draw treatment con-
  clusions beyond those supported by the study design. In Chapter 9
  we discuss methods for exploratory data analysis.
  8.2
  Historical controls
  As noted in Chapter 3, any nonrandomized choice of a control group
  will be systematically diﬀerent from the e