title: Hypothesis testing I: proportions.
abstract: Statistical inference involves two analysis methods: estimation and hypothesis testing, the latter of which is the subject of this article. Specifically, Z tests of proportion are highlighted and illustrated with imaging data from two previously published clinical studies. First, to evaluate the relationship between nonenhanced computed tomographic (CT) findings and clinical outcome, the authors demonstrate the use of the one-sample Z test in a retrospective study performed with patients who had ureteral calculi. Second, the authors use the two-sample Z test to differentiate between primary and metastatic ovarian neoplasms in the diagnosis and staging of ovarian cancer. These data are based on a subset of cases from a multiinstitutional ovarian cancer trial conducted by the Radiologic Diagnostic Oncology Group, in which the roles of CT, magnetic resonance imaging, and ultrasonography (US) were evaluated. The statistical formulas used for these analyses are explained and demonstrated. These methods may enable systematic analysis of proportions and may be applied to many other radiologic investigations.
authors.affiliation: Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. zou@bwh.harvard.edu.
authors.forename: Kelly H
authors.initials: KH
authors.lastname: Zou
authors.forename: Julia R
authors.initials: JR
authors.lastname: Fielding
authors.forename: Stuart G
authors.initials: SG
authors.lastname: Silverman
authors.forename: Clare M C
authors.initials: CM
authors.lastname: Tempany
mesh_terms: D003952:Diagnostic Imaging; D005260:Female; D006801:Humans; D009367:Neoplasm Staging; D010051:Ovarian Neoplasms / Q000175:diagnosis*; D013223:Statistics as Topic