title: Scoring in genetically modified organism proficiency tests based on log-transformed results.
abstract: The study considers data from 2 UK-based proficiency schemes and includes data from a total of 29 rounds and 43 test materials over a period of 3 years. The results from the 2 schemes are similar and reinforce each other. The amplification process used in quantitative polymerase chain reaction determinations predicts a mixture of normal, binomial, and lognormal distributions dominated by the latter 2. As predicted, the study results consistently follow a positively skewed distribution. Log-transformation prior to calculating z-scores is effective in establishing near-symmetric distributions that are sufficiently close to normal to justify interpretation on the basis of the normal distribution.
authors.affiliation: University of London, Birkbeck College, School of Biological and Chemical Sciences, Malet St, London, United Kingdom.
authors.forename: Michael
authors.initials: M
authors.lastname: Thompson
authors.forename: Stephen L R
authors.initials: SL
authors.lastname: Ellison
authors.forename: Linda
authors.initials: L
authors.lastname: Owen
authors.forename: Kenneth
authors.initials: K
authors.lastname: Mathieson
authors.forename: Joanne
authors.initials: J
authors.lastname: Powell
authors.forename: Pauline
authors.initials: P
authors.lastname: Key
authors.forename: Roger
authors.initials: R
authors.lastname: Wood
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Damant
mesh_terms: D003627:Data Interpretation, Statistical; D005504:Food Analysis; D030841:Food, Genetically Modified; D016013:Likelihood Functions; D015233:Models, Statistical; D016011:Normal Distribution; D030781:Organisms, Genetically Modified; D016133:Polymerase Chain Reaction; D015203:Reproducibility of Results; D016008:Statistical Distributions