forestSummarize {NMsim} | R Documentation |
Summarize simulated exposures relative to reference subject
Description
Summarize simulated exposures relative to reference subject
Usage
forestSummarize(data, funs.exposure, cover.ci = 0.95, by, as.fun)
Arguments
data |
Simulated data to process. This data.frame must contain must contain multiple columns, as defined by 'NMsim::forestDefineCovs()'. |
funs.exposure |
A named list of functions to apply for derivation of exposure metrics. |
cover.ci |
The coverage of the confidence intervals. Default is 0.95. |
by |
a character vector of column names to perform all calculations by. This could be sampling subsets or analyte. |
as.fun |
The default is to return data as a 'data.frame'. Pass a function (say 'tibble::as_tibble') in as.fun to convert to something else. If data.tables are wanted, use 'as.fun="data.table"'. The default can be configured using 'NMdataConf()'. |
Details
This function is part of the workflow provided by NMsim to generate forest plots - a graphical representation of the estimated covariate effects and the uncertainty of those effect estimates. 'forestDefineCovs()' helps construct a set of simulations to perform, simulation methods like 'NMsim_VarCov' and 'NMsim_NWPRI' can perform siulations with parameter uncertainty, and 'forestSummarize()' can then summarize those simulation results into the numbers to plot in a forest plot. See the NMsim vignette on forest plot generation available on the NMsim website for a step-by-step demonstration.
The following columns are generated by 'forestDefineCovs()' and are expected to be present. Differences within any of them will lead to separate summarizing (say for as covariate value to be plotted):
'model': A model identifier - generated by 'NMsim()'.
'type': The simulation type. "ref" for reference subject, "value" for any other. This is generated by 'forestDefineCovs()'.
'covvar': The covariate (of interest) that is different from the reference value in the specific simulation. Example: "WT"
'covlabel': Label of the covariate of interest. Example: "Bodyweight (kg)"
'covref': Reference value of the covariate of interest. Example: 80
'covval': Value of the covariate of interest (not reference). Example 110.
Value
A data.frame