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Hypothesis Testing I: Proportions¹

¹ From the Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Mass (K.H.Z., J.R.F., S.G.S., C.M.C.T.); and Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115 (K.H.Z.). Received September 10, 2001; revision requested November 8; revision received December 12; accepted December 19. Supported in part by Public Health Service Grant NIH-U01 CA9398-03 awarded by the National Cancer Institute, Department of Health and Human Services. Address correspondence to K.H.Z. (e-mail: zou@bwh.harvard.edu).

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.

© RSNA, 2003

Index terms: Statistical analysis

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