Concentration models settings

Calculation settings

Table 52 Calculation settings for module Concentration models.

Name	Type	Description
Seed for pseudo-random number generator	Numeric	A value of 0 will use a pseudo-random seed in each run, a value > 0 will provide the same results in a repeated run.
Exposure type	ExposureType	The type of exposure considered in the assessment; acute (short term) or chronic (long-term).
Selected tier	SettingsTemplateType	Specifies all module settings should be set according to a pre-defined tier or using custom settings.
Concentration model types per food-substance combination	ConcentrationModelTypeFoodSubstance	The concentration model types used for food/substance combinations.
Default concentration model	ConcentrationModelType	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	Boolean	Use the MRL as fallback model in case the occurrence data is insufficient for other concentration modelling options.
Restrict LOR imputation to authorised uses	Boolean	Specifies whether imputation of factor x LOR should be limited to authorised uses only.
Censored values replacement	NonDetectsHandlingMethod	How to replace censored values (when not co-modelled, as in censored models).
Factor f (f x LOR or f x LOD or LOD + f x (LOQ - LOD)	Numeric	Replace censored values by Limit of reporting (LOR), Non-detects (LOD) or Non-quantifications (LOQ) times this factor. Constant (f), e.g. 0.5.
MRL Factor (f x MRL)	Numeric	Use f x MRL as concentration estimate of the MRL models.
Sample based	Boolean	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)	Boolean	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	Boolean	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	Boolean	Use of occurrence frequencies (e.g., agricultural use frequencies) is relevant for imputation of censored values in the concentration data. Part of the observed censored values 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.
Total diet study concentration data	Boolean	Specifies whether exposure is based on sampling data from total diet studies.
Multiple substances analysis	Boolean	Specifies whether the assessment involves multiple substances.
Compute cumulative exposures	Boolean	Specifies whether the assessment involves multiple substances and results should be cumulated over all substances.

Uncertainty settings

Table 53 Uncertainty settings for module Concentration models.

Name	Type	Description
Parametric uncertainty	Boolean	For resample concentrations: specifies whether the uncertainty assessment is based on a parametric approach.
Resample concentrations	Boolean	Specifies whether concentrations are resampled by empirical bootstrap or using a parametric uncertainty model.