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Data handling

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, 26-27 January 2005. Outline. Data quality Replicates Concentrations below LOD or LOQ

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Data handling

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  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, 26-27 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 sample <LOD just before & after detectable amount to 0.5 LOD • Omit all other samples < LOD (exceptions) • Set concentrations between LOD and LOQ to measured value or 0.5 x (LOD+LOQ)

  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 days DT50 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 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. M0 fixed: DT50 = 48 days

  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 No transformation: DT50 = 51 days No transformation: DT50 = 54 days Log transformed: DT50 = 57 days Log transformed: DT50 = 108 days Always use unweighted data as a first step! 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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