Linked Life Data

19921345

Source:http://linkedlifedata.com/resource/pubmed/id/19921345

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2010-2-17
pubmed:abstractText
In the 1920s, Ronald Fisher developed the theory behind the p value and Jerzy Neyman and Egon Pearson developed the theory of hypothesis testing. These distinct theories have provided researchers important quantitative tools to confirm or refute their hypotheses. The p value is the probability to obtain an effect equal to or more extreme than the one observed presuming the null hypothesis of no effect is true; it gives researchers a measure of the strength of evidence against the null hypothesis. As commonly used, investigators will select a threshold p value below which they will reject the null hypothesis. The theory of hypothesis testing allows researchers to reject a null hypothesis in favor of an alternative hypothesis of some effect. As commonly used, investigators choose Type I error (rejecting the null hypothesis when it is true) and Type II error (accepting the null hypothesis when it is false) levels and determine some critical region. If the test statistic falls into that critical region, the null hypothesis is rejected in favor of the alternative hypothesis. Despite similarities between the two, the p value and the theory of hypothesis testing are different theories that often are misunderstood and confused, leading researchers to improper conclusions. Perhaps the most common misconception is to consider the p value as the probability that the null hypothesis is true rather than the probability of obtaining the difference observed, or one that is more extreme, considering the null is true. Another concern is the risk that an important proportion of statistically significant results are falsely significant. Researchers should have a minimum understanding of these two theories so that they are better able to plan, conduct, interpret, and report scientific experiments.
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-10383371, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-11159626, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-11341427, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-15131445, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-1729024, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-18566874, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-18582619, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-19124547, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-3342551, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-7025843, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-7641425, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-8070215, http://linkedlifedata.com/resource/pubmed/commentcorrection/19921345-9314400
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1528-1132
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
468
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
885-92
pubmed:dateRevised
2011-7-25
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
P value and the theory of hypothesis testing: an explanation for new researchers.
pubmed:affiliation
Département de Biostatistique et Informatique Médicale, INSERM-UMR-S 717, AP-HP, Université Paris 7, Hôpital Saint Louis, 1, Avenue Claude-Vellefaux, Paris Cedex 10 75475, France. djmbiau@yahoo.fr
pubmed:publicationType
Journal Article