title: What is the Proper Sample Size for Studies of Periodontal Treatment?
abstract: Small sample sizes are a common problem in biomedical research, and the periodontal literature is no exception. It is a problem leading to not only reduced statistical power but also an inappropriate statistical inference of a treatment effect. Using statistical methods with an insufficient sample size may give rise to an increased chance of falsely detecting treatment efficacy. This article provides some guidelines to cope with the small sample size problem. The authors discuss adequate sample sizes in several statistical tests and then suggest alternative statistical methods that are valid with a small sample size.
authors.affiliation: Department of Biostatistics, University at Buffalo, The State University of New York, 706 Kimball Tower, Buffalo, NY 14214-3000, USA. Electronic address: jinheeyu@buffalo.edu.
authors.forename: Jihnhee
authors.initials: J
authors.lastname: Yu
authors.affiliation: Department of Biostatistics, University at Buffalo, The State University of New York, 706 Kimball Tower, Buffalo, NY 14214-3000, USA.
authors.forename: Luge
authors.initials: L
authors.lastname: Yang
authors.affiliation: Department of Biostatistics, University at Buffalo, The State University of New York, 706 Kimball Tower, Buffalo, NY 14214-3000, USA.
authors.forename: Alan D
authors.initials: AD
authors.lastname: Hutson
mesh_terms: D016000:Cluster Analysis; D018865:Dental Research / Q000592:standards* / Q000706:statistics & numerical data*; D006801:Humans; D010517:Periodontics; D018401:Sample Size; D018709:Statistics, Nonparametric
keywords: Bootstrap method; Exact nonparametric tests; Periodontal treatment; Rules of thumb for the sufficient sample; Small sample size