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Recent recommendations of the Consultative Committee for Length (CCL) regarding strategies for evaluating key comparison data

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Jennifer E Decker1,4, N Brown2, Maurice G Cox3, A G Steele1 and R J Douglas2

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[1]

Laboratory effects models for interlaboratory comparisons

Blaza Toman and Antonio Possolo  Accreditation and Quality Assurance 2009 
CrossRef 
[2]

A comparison of location estimators for interlaboratory data contaminated with value and uncertainty outliers

David Lee Duewer  Accreditation and Quality Assurance 2008 
CrossRef 
[3]

Analysing redundancy in a line scale comparison using Monte Carlo methods

J E Decker et al  Measurement Science and Technology 2008  19 064005
IOPscience 
[4]

Establishing confidence from measurement comparisons

A G Steele and R J Douglas  Measurement Science and Technology 2008  19 064003
IOPscience 
[5]

Avoiding a complex reference value

R J Douglas and A G Steele  Metrologia 2008  45 L13
IOPscience 
[6]

Measurement science and the linking of CIPM and regional key comparisons

Jennifer E Decker et al  Metrologia 2008  45 223
IOPscience 
[7]

The definition of the measurand in key comparisons: lessons learnt with thermal standards

F Pavese  Metrologia 2007  44 327
IOPscience 
[8]

The evaluation of key comparison data: determining the largest consistent subset

Maurice G Cox  Metrologia 2007  44 187
IOPscience 
crossref member

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