PDF icon Download PDF
Facial Plast Surg 2002; 18(2): 087-094
DOI: 10.1055/s-2002-32198
Copyright © 2002 by Thieme Medical Publishers, Inc., 333 Seventh Avenue, New York, NY 10001, USA. Tel.: +1(212) 584-4662

Statistical Inference in Facial Plastic Surgery: Perspectives and Alternatives

Christopher S. Hollenbeak1, 2 , Thomas S. Wasser2 , Robert X. Murphy, Jr.3 , Lawrence C. Kleinman2 , Brendan C. Stack, Jr.4
  • 1Departments of Surgery and Health Evaluation Sciences, Penn State College of Medicine, Hershey, PA
  • 2Health Studies Unit, Lehigh Valley Hospital, Allentown, PA
  • 3Department of Surgery, Lehigh Valley Hospital, Allentown, PA
  • 4Division of Otolaryngology-Head and Neck Surgery, Penn State College of Medicine, Hershey, PA
Further Information

Publication History

Publication Date:
13 June 2002 (online)

Also available atMedOne
   Permissions and Reprints
Preview

ABSTRACT

Facial plastic surgeons often must make decisions with imperfect information. Statistical inference is fundamentally the practice of using data to draw conclusions about uncertain phenomena. It is important, therefore, that facial plastic surgeons engaged both in clinical practice and in research have an understanding of statistical concepts to conduct research with results that are meaningful, to assess the validity of published research, and to adopt the most effective techniques and treatments. The purpose of this article is to provide an overview of classical statistical methods that are encountered frequently in facial plastic surgery research, discuss issues of interpretation of results, and introduce an alternative paradigm for conducting statistical inference.

KEYWORDS

Statistics - facial plastic surgery - Bayesian analysis

REFERENCES

  • 1 Kuzma J W. Basic Statistics for the Health Sciences.  Mountain View, CA: Mayfield; 1984
    Search in Google Scholar
  • 2 Mauger D T, Kauffman G L. Statistical considerations. In: Souba WW, Wilmore DW, eds. Surgical Research London: Academic Press 2001 0: 71-80
    Search in Google Scholar
  • 3 DeGroot M H. Probability and Statistics, 2nd ed.  Reading, MA: Addison-Wesley 1986
    Search in Google Scholar
  • 4 Mauger D T, Kauffman G L. Statistical analysis-specific statistical tests: indications for use. In: Souba WW, Wilmore DW, eds. Surgical Research London: Academic Press 2001 : 1201-1215
    Search in Google Scholar
  • 5 Dawson-Sanders B, Trapp R G. Basic and Clinical Biostatistics, 2nd ed. Norwalk, CT: Appleton & Lange 1994
    Search in Google Scholar
  • 6 O'Hagan A. Kendall's Advanced Theory of Statistics: Bayesian Inference.  New York: John Wiley & Sons; 1994
    Search in Google Scholar
  • 7 Altman D G. Practical Statistics for Medical Research.  London: Chapman & Hall; 1991
    Search in Google Scholar
  • 8 Conover W J. Practical Nonparametric Statistics, 3rd ed.  New York: John Wiley & Sons 1999
    Search in Google Scholar
  • 9 Gelman A, Carlin J B, Stern H S, Rubin D B. Bayesian Data Analysis.  London: Chapman & Hall; 1995
    Search in Google Scholar
  • 10 Altman D G. The scandal of poor medical research.  Br Med J . 1994;  308 283-284
    PubMedSearch in Google Scholar
  • 11 Altman D G. Statistics in medical journals.  Stat Med . 1982;  1 59-71
    PubMedSearch in Google Scholar
  • 12 Anderson B. Methodological Errors in Medical Research.  An Incomplete Catalogue. Oxford: Blackwell; 1990
    Search in Google Scholar