CIND e InterCinD 15 years of statistical elaboration and innovation

Transcription

1 INTERCIND annual meeting Venezia POP s day: Diossine, POPs, PFAS, distruttori endocrini emergenti e vecchi amici. Nel 2018 la prevenzione dov è? 1 June 2018, Venezia CIND e InterCinD 15 years of statistical elaboration and invation Simone Libralato Istituto Nazionale di Oceagrafia e di Geofisica Sperimentale OGS Dipartimento di Oceagrafia, Trieste slibralato@ogs.trieste.it

2 History Cind 7 Cind 1 Intercind 6 Intercind

3 PCDD/F PCDD/F PCBs dioxin-like PAHs PCDD/F PCBs dioxin-like PCBs ICES-6 PAHs PBDE PCDD/F PCBs dioxin-like PCBs ICES-6 PAHs PBDE Heavy metals History 1 Cind 7 Cind 1 Intercind 6 Intercind Sediment Sediment Fly Ash Sediment Fly Ash Food feed

4 Statistical data treatment in Intercind is INSPIRED by ISO 13528/2015 and IUPAC Guidelines Peculiarities of INTERCIND 1) Natural matrixes (unkwn concentration) 2) Replicates (accuracy&precision) 3) Statistical treatment (Determination of extremes and outliers with n-parametric method) PTP 0007 The interlaboratory circuit is organized in agreement with international guidelines relative to the organization and management of interlaboratory circuits UNI CEI EN ISO/IEC 17043: 2010

5 First phase CIND Data from Labs First check Intercind input form Data problem? CIND parametric method Performance evaluation Precision (r-range) Accuracy (z-score) First Statistical analysis data outlier? Data removed Valid data Statistical analysis

6 Data from Labs Second phase CIND First check First Statistical analysis Intercind input form Data problem? Intercind/CIND n paramertic method data outlier? Data removed Performance evaluation Precision (r-range) Accuracy (z-score) Valid data Statistical analysis

7 Data from Labs The procedure First check First Statistical analysis Intercind input form data outlier? Data problem? Intercind statistical method Data removed Performance evaluation Precision (r-range) Accuracy (z-score) 2 s σ ' p = s + σ 2 p Use σp Somog<=0. 3 σp Valid data Statistical analysis Assigned value and its uncertainty Simme try of data? Mean/me dian Nlab> 15 RSD%< 55% Outlier <20% u<0.3σp median; kernel pliots Use media n No assigned value No assigned value No assigned value No assigned value No assigned value

8 determination assigned value From: Piotr Robouch (JRC) - 9th International Workshop on Proficiency Testing (9-12 October 2017, Portoroz, Slovenia)

9 Determination of assigned values What is the most likely TRUE value? What are the UGLY data? What are the BAD data? number of laboratories median average 2,3,7,8, TeCDF (ng/g) The Bad The Good The Ugly In particular the main first step is to identify main errors due to: misreporting, rough errors, instrumental mistakes. Of course considering that error ise on data is always unavoidable.

10 definition of outliers for data x i,k, : 1-7th Cind 2 > x s xi, k, x i, k, > + 2 x s In case of data more disperse the method needed double application. The problem defining outliers Mean- 2SD <0.01 <0.5 <1 Mean-SD <1.5 <2 <2.5 <3 Mean <3.5 <4 <4.5 <5 Mean+SD <5.5 <6 <6.5 <7 <7.5 Mean+ 2SD <8 <8.5 <9 <9.5 These are NOT defined as ouliers These are defined as ouliers

11 Data stats: µ = ; σ = Data stats: µ = ; σ = Intercind concentration Data synthetically generated: n=150; µ = 1; σ = 0.2

12 Data stats: µ = ; σ = Data stats: µ = ; σ = Algorithm A ISO concentration Data synthetically generated: n=150; µ = 1; σ = 0.2

13 1 st Intercind (2013) Is based on n-parametric measures: median, and interquartile range Q 75 Q25 = U M and quartiles Q25, Q75 Q 25 3 U < xi, k, Q U < xi, k, Extremes Outliers x x i, k, i, k, > Q U > Q U Median Q U Q75+ 3 U Q2520 Q Data here are defined as extremes <0.01 <0.5 <1 <1.5 <2 <2.5 <3 <3.5 <4 <4.5 <5 <5.5 <6 <6.5 <7 <7.5 <8 <8.5 Number of laboratories Data here are defined outliers <9 <9.5

14 Data stats: µ = ; σ = Data stats: µ = ; σ = Intercind concentration Data synthetically generated: n=150; µ = 1; σ = 0.2

15 Comparing methods Data synthetically generated: n=150; µ = 1; σ = 0.2

16 Intercind statistical method Synthetic data

17 Intercind statistical method SED_123789HxCDF

18 Robust method?

19 Robust method? The Intercind methodology is simple, easy to understand, robust with up to 20% of extreme (infinity []) values. Do we want to have robust estimates by consensus from data in which > 20% are absurd?

20 INTERCIND annual meeting Venezia POP s day: Diossine, POPs, PFAS, distruttori endocrini emergenti e vecchi amici. Nel 2018 la prevenzione dov è? 1 June 2018, Venezia CIND e InterCinD 15 years of statistical elaboration and invation Simone Libralato Istituto Nazionale di Oceagrafia e di Geofisica Sperimentale OGS Dipartimento di Oceagrafia, Trieste slibralato@ogs.trieste.it