Skip Navigation

JNCI Journal of the National Cancer Institute 2004 96(22):1722-1723; doi:10.1093/jnci/djh327
© 2004 by Oxford University Press
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by Wacholder, S.
Right arrow Articles by Rothman, N.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Wacholder, S.
Right arrow Articles by Rothman, N.
Related Collections
Right arrowRelated Correspondence
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2004 Oxford University Press

CORRESPONDENCE

RESPONSE: Re: Assessing the Probability That a Positive Report is False: An Approach for Molecular Epidemiology Studies

Sholom Wacholder, Stephen Chanock, Montserrat Garcia-Closas, Hormuzd A. Katki, Laure El ghormli, Nathaniel Rothman

Affiliations of authors: Biostatistics Branch (SW, HAK), Core Genotype Facility (SC), Hormonal and Reproductive Epidemiology Branch (MGC), and Occupational and Environmental Epidemiology Branch (NR), Division of Cancer Epidemiology and Genetics, and Pediatric Oncology Branch, Center for Cancer Research (SC), National Cancer Institute, National Institutes of Health, Bethesda, MD; George Washington University, Biostatistics Center, Rockville (LE)

Correspondence to: Sholom Wacholder, PhD, Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892-7244 (e-mail: wacholder@nih.gov)

The first 10% of the full text of this article appears below.

Dr. Dubben notes that a study with higher statistical power will have a lower false-positive report probability (FPRP) than a study with lower statistical power, as seen in equation 1 and in figures 1 and 2 of our original paper (1). He is puzzled, however, by figure 5 (1), which shows FPRP increasing with increasing statistical power.

Our paper's figure 5 (1. . . [Full Text of this Article]


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?

Related Correspondence

Re: Assessing the Probability That a Positive Report is False: An Approach for Molecular Epidemiology Studies
Hans-Hermann Dubben
J Natl Cancer Inst 2004 96: 1722. [Extract] [Full Text] [PDF]