Experimental Design Problems

Interpretation of Statistical Arithmetic
  • Elmer C. Hall
  • C. Alex McMahan


When first asked to speak on experimental design problems in the quantitative evaluation of atherosclerosis, particularly in progression/regression studies, my reaction was that I didn’t know enough about the area to do it justice. I still don’t. (Of course, I knew about least squares regression but least squares progression was not in my statistical vocabulary.)


Standard Deviation Coronary Atherosclerosis Effective Sample Size Statistical Arithmetic Coronary Artery Surgery Study 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Glantz SA (1980) Biostatistics: how to detect, correct, and prevent errors in the medical literature. Circulation 61:1–7PubMedGoogle Scholar
  2. 2.
    Sheehan TJ (1980) The medical literature: let the reader beware. Arch Intern Med 140:472–474PubMedCrossRefGoogle Scholar
  3. 1.
    McGill HC, McMahan CA, Wene JD (1981) Unresolved problems in the diet-heart issue. Arteriosclerosis 1: 164–176PubMedCrossRefGoogle Scholar
  4. 2.
    Good PI (1979) Detection of a treatment effect when not all experimental subjects will respond to treatment. Biometrics 35: 484–489CrossRefGoogle Scholar
  5. 3.
    Fishman AP, Berne RM, Morgan HE (1981) By the numbers... Am J Physiol 241: C91–C92Google Scholar

Copyright information

© Springer-Verlag New York Inc. 1983

Authors and Affiliations

  • Elmer C. Hall
  • C. Alex McMahan

There are no affiliations available

Personalised recommendations