How not to interpret a P value? [3]

Journal of the National Cancer Institute

Volumn 99, Issue 4, 2007, Pages 332-333

  Pharoah, Paul ^a,b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTIC METHOD; ANALYTICAL ERROR; BAYES THEOREM; FALSE POSITIVE RESULT; HYPOTHESIS; LETTER; NULL HYPOTHESIS; PREVALENCE; PRIORITY JOURNAL; PROBABILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL SIGNIFICANCE; CLINICAL TRIAL; HUMAN; LABORATORY DIAGNOSIS; METHODOLOGY; NOTE; STANDARD;

ANTINEOPLASTIC AGENT;

ANTINEOPLASTIC AGENTS; BAYES THEOREM; CLINICAL TRIALS; FALSE POSITIVE REACTIONS; HUMANS; PROBABILITY; SENSITIVITY AND SPECIFICITY;

EID: 33847794263     PISSN: 00278874     EISSN: 14602105     Source Type: Journal    
DOI: 10.1093/jnci/djk061     Document Type: Letter

References (3)

1. Beckman M. Are Bayes' days upon us? Statistical methods could change the conduct of clinical trials. J Natl Cancer Inst 2006;98: 1512-3.
2. Thompson WC, Schumann E. Interpretation of statistical evidence in criminal trials: The prosecutor's fallacy and the defense attorney's fallacy. Law Hum Behav 1987;11:167-87.
3. Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N. Assessing the probability that a positive report is false: An approach for molecular epidemiology studies. J Natl Cancer Inst 2004;96:434-42.