Concentration models settings

Calculation settings

Table 37 Calculation settings for module Concentration models.
Name Description
Concentration model tier
Custom model, or set according to EFSA Guidance 2012. Note: you may need to set the tier separately in sub-modules.
Default concentration model
The concentration model type that will be used as default for all food/substance combinations. If this model type cannot be fitted, e.g., due to a lack of data, a simpler model will be chosen automatically as a fall-back.
Include MRL fallback model
Use the MRL as fallback model in case the occurrence data is insufficient for other concentration modelling options.
Restrict LOR imputation to authorised uses
Specifies whether imputation of factor x LOR should be limited to authorised uses only.
Non-detects replacement
How to replace non-detects (when not co-modelled, as in censored models).
Factor f (f x LOR)
Replace non-detects by Limit Of Reporting (LOR) times this factor. Constant (f), e.g. 0.5.
MRL Factor (f x MRL)
Use f x MRL as concentration estimate of the MRL models.
Sample based
Include co-occurrence of substances in samples in simulations. If checked, substance residue concentrations are sampled using the correlations between values on the same sample. If unchecked, any correlation between substances is ignored, substance residue concentrations are sampled ignoring the correlations between values on the same sample.
Impute missing values from available values (if unchecked, missing values are imputed with 0)
If checked, in procedure of EFSA Guidance 2012, Appendix 1, impute missing values using substance based concentration models. If unchecked, missing values are imputed by 0.
Correlate imputed values with sample potency
If checked, in procedure of EFSA Guidance 2012, Appendix 1, correlate high imputed values with high cumulative potency samples. If unchecked, random imputation.
Use occurrence frequencies for imputation
Use of occurrence frequencies (e.g., agricultural use frequencies) is relevant for imputation of non-detects in the concentration data. Part of the observed non-detects and missing values may be imputed with zero when the occurrence frequency is smaller than 100%. If checked, occurrence frequencies are expected as input of this action, otherwise 100% potential presence is assumed for all substances on all foods.

Uncertainty settings

Table 38 Uncertainty settings for module Concentration models.
Name Description
Parametric uncertainty
For resample concentrations: specifies whether the uncertainty assessment is based on a parametric approach.