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Data handling Sabine Beulke, CSL, York, UK FOCUS Work Group on Degradation Kinetics Estimating Persistence and Degradation Kinetics from Environmental.

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Presentation on theme: "Data handling Sabine Beulke, CSL, York, UK FOCUS Work Group on Degradation Kinetics Estimating Persistence and Degradation Kinetics from Environmental."— Presentation transcript:

1 Data handling Sabine Beulke, CSL, York, UK FOCUS Work Group on Degradation Kinetics Estimating Persistence and Degradation Kinetics from Environmental Fate Studies in EU Registration Brussels, January 2005

2 Outline Data quality Replicates Concentrations below LOD or LOQ Experimental artefacts Outliers Time zero samples Data weighting For more information see Chapter 6.1 of the FOCUS report

3 Data quality Dissipation pattern and - for metabolites and sediment data - the increase, plateau and decline phase must be clearly established No. of data points (n) >> no. of parameters (p) (theoretical minimum n = p+1, but this is often not sufficient) The better the quality the smaller the no. of datapoints needed

4 Replicates Use true replicates individually in the optimisation Average replicate analytical results from same sample prior to curve fitting Average all replicates prior to calculating 2 statistics

5 Concentrations below LOD or LOQ Parent in soil, total water-sediment system, water column Set all concentrations between LOD and LOQ to measured value or 0.5 x (LOD+LOQ) Set first sample < LOD to 0.5 x LOD Omit samples after first non-detect unless later samples > LOQ Set to measured value Set to 0.5 x LOD Omit

6 Concentrations below LOD or LOQ Metabolite in soil and parent and metabolite in sediment Set time zero samples < LOD to 0 Set concentrations between LOD and LOQ to measured value or 0.5 x (LOD+LOQ) Set sample { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/741341/2/slides/slide_5.jpg", "name": "Concentrations below LOD or LOQ Metabolite in soil and parent and metabolite in sediment Set time zero samples < LOD to 0 Set concentrations between LOD and LOQ to measured value or 0.5 x (LOD+LOQ) Set sample

7 Experimental artefacts Discard results clearly arising from analytical or procedural errors before analysis If microbial activity declined significantly during study: Include all data initially, then exclude later sampling points and repeat fitting

8 DT50 42 daysDT50 34 days Outliers Include all data in curve fitting as a first step Omit outliers based on expert judgement Statistical outlier test where possible

9 Time zero samples Include initial amount of parent (soil, total w/s system and water column) in parameter estimation as a first step M0 variable: DT50 = 68 days M0 fixed: DT50 = 48 days Note: This hypothetical dataset is not described well by SFO kinetics and is only used to illustrate the effect of fixing or estimating the initial concentration.

10 Time zero samples Add time-zero concentrations of metabolites > 0 to parent unless due to impurity in application solution Add time-zero concentrations > 0 of parent or metabolite in sediment to water M0 variable: DT50 = 68 days M0 fixed: DT50 = 48 days Note: This hypothetical dataset is not described well by SFO kinetics and is only used to illustrate the effect of fixing or estimating the initial concentration.

11 Data weighting Always use unweighted data as a first step! No transformation: DT50 = 51 days Log transformed: DT50 = 57 days No transformation: DT50 = 54 days Log transformed: DT50 = 108 days Note: This hypothetical dataset is not described well by SFO kinetics and is only used to illustrate the effect of log-transformation.


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