LEEM_Concentration: Concentration Summary Statistics to Weighted Concentration...

In AlexanderEast/LEEMR: Exposure estimates from sparse concentration summary statics

Concentration Summary Statistics to Weighted Concentration Estimates

Description

A function which creates synthetic lognormal data from a dataframe of summary statistic concentration data, exposure factors, a selected weighting column, and n number of points for a single media and single chemical.

This model is based on methods described in Egeghy & Lorber (2011) , Lorber & Egeghy (2011) , and East et al. (2021).

The series of estimating equations for geometric mean (GM) and geometric standard deviation (GSD) is primarily adapted from Pleil et al. (2014).

Accepted Units: ng/m3, ug/m3, pg/ml, ng/mL, ug/L, ng/L, pg/g, ug/kg, ng/g

Concentration output: ng/m3, ng/L, or ng/g

The function returns a list of dataframes:

Summary: mean, min, 10th percentile, median, 75th percentile, 95th percentile, and max for concentration and exposure across each media, pathway, and chemical entered.

Used Input: The input data for which GM and GSDs could be estimated.

Excluded Input: The input data for which GM and GSDs could not be estimated.

Used Dataset Counts: Counts of used datasets by chemical and media.

Raw: Raw data for plotting.

Metadata: Time and date, chemicals, media, n, and seed used in the run.

Usage

LEEM_Concentration(data, wtcol, n, seed = NULL)

This function is used to summarize lognormally distributed concentration data in similar media.
An example using PFOA in serum is provided in the Examples section below.

Arguments

data = A dataframe of one media containing the following columns: Chemical, Media, Units, Sample Size, Min, Max, Median, Mean, SD, GM, GSD, P10, P25, P75, P90, P95, P99. Column names are not case sensitive.

wtcol = A character input for the name of the 'weighting' column (often 'sample size').

n = The number of generated concentration and exposure outcomes generated by rlnorm().

seed = Optional input to ensure or characterize variability between runs. Set by default to 12345.

Examples

# using the Example dataset "LEEMR_Example_Data":
# dataframe "serum" used as data argument
# specifying the column "sample size" to weight datasets
# setting n = 1000
# no argument provided for 'seed', defaulting to "12345"

LEEM_Concentration(LEEMR_Example_Data$Serum,
                   "sample size",
                   1000)

AlexanderEast/LEEMR documentation built on May 21, 2022, 10:10 a.m.