Statistical inference in facial plastic surgery: Perspectives and alternatives

Christopher S. Hollenbeak, Thomas S. Wasser, Robert X. Murphy, Lawrence C. Kleinman, Brendan C. Stack

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)87-93
Number of pages7
JournalFacial Plastic Surgery
Volume18
Issue number2
DOIs
StatePublished - 2002

All Science Journal Classification (ASJC) codes

  • Surgery

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