title: Statistical analysis of surgical pathology data using the R program.
abstract: An understanding of statistics is essential for analysis of many types of data including data sets typically reported in surgical pathology research papers. Fortunately, a relatively small number of statistical tests apply to data relevant to surgical pathologists. An understanding of when to apply these tests would greatly benefit surgical pathologists who read and/or write papers. In this review, we show how the publicly available statistical program R can be used to analyze recently published surgical pathology papers to replicate the p-values and survival curves presented in these papers. Areas covered include: T-test, chi-square and Fisher exact tests of proportionality, Kaplan-Meier survival curves, the log rank test, and Cox proportional hazards.
authors.affiliation: Department of Pathology, Stanford University School of Medicine, CA 94305, USA.
authors.forename: Justin
authors.initials: J
authors.lastname: Cuff
authors.forename: John P T
authors.initials: JP
authors.lastname: Higgins
mesh_terms: D006801:Humans; D053208:Kaplan-Meier Estimate; D010340:Pathology, Surgical / Q000379:methods*; D016016:Proportional Hazards Models; D012984:Software; D013223:Statistics as Topic