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PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
18
pubmed:dateCreated
2010-8-3
pubmed:abstractText
The cumulative summation (CUSUM) test is increasingly being used in medicine to monitor a wide variety of processes such as cardiac surgery or disease outbreaks. The CUSUM sequentially tests the null hypothesis that the process is in control, i.e. its mean is equal to a given target. Thus, it detects when the process changes to an out of control state. Conversely, monitoring the learning curve requires detecting the time when the process reaches an in control state. In this work we develop an alternative to the CUSUM, the learning curve CUSUM (LC-CUSUM), that serves to detect when a process deviates from an out of control state to an in control state. The test is based on a two one-sided tests procedure where the null hypothesis is that the process is out of control. This can be written as H(0): |mu-mu(0)|> or =delta tested against H(1): |mu-mu(0)|< delta. The null hypothesis is thus the union of two one-sided hypotheses and is rejected when both are rejected. A CUSUM test statistic is then constructed for each hypothesis in a traditional way. The properties of the test are investigated through numerical simulations, and are illustrated on the learning curve of an endoscopist performing endoscopic retrograde cholangiopancreatographies for biliary tract disorders.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1097-0258
pubmed:author
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
29
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1900-9
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
A method for monitoring a process from an out of control to an in control state: Application to the learning curve.
pubmed:affiliation
Département de Biostatistique et Informatique Médicale, Hôpital Saint-Louis, AP-HP, Paris, France. djmbiau@yahoo.fr
pubmed:publicationType
Journal Article