title: Statistical inference in facial plastic surgery: perspectives and alternatives.
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.
authors.affiliation: Department of Surgery, Penn State College of Medicine, Hershey, PA 17033, USA.
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Hollenbeak
authors.forename: Thomas S
authors.initials: TS
authors.lastname: Wasser
authors.forename: Robert X
authors.initials: RX
authors.lastname: Murphy
authors.forename: Lawrence C
authors.initials: LC
authors.lastname: Kleinman
authors.forename: Brendan C
authors.initials: BC
authors.lastname: Stack
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016009:Chi-Square Distribution; D003625:Data Collection; D003657:Decision Making; D005145:Face / Q000601:surgery*; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data; D011336:Probability; D019651:Plastic Surgery Procedures / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012107:Research Design; D018709:Statistics, Nonparametric