Generate data frame of generic footnote equations to append to parameter tables.
param_notes(.ci = 95, .zscore = NULL)specify 90 or 95 percent confidence interval (default 95%)
z-score for the specified confidence interval. Only needed for confidence intervals that are NOT 90 or 95 percent
#Using output from `format_param_table` (defineOut),
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
paramEst <- utils::read.csv(system.file("model/nonmem/param_est.csv", package = "pmparams"))
paramKey <- system.file("model/nonmem/pk-parameter-key-new.yaml", package = "pmparams")
defineOut <- define_param_table(.estimates = paramEst, .key = paramKey, .ci = 95, .zscore = NULL)
#> [1] "Parameter table yaml path provided: /data/pmparams/inst/model/nonmem/pk-parameter-key-new.yaml"
data <- format_param_table(.df = defineOut)
#To make random effects table and add relevant footnotes:
footnotes = param_notes()
table <- make_pmtable(.df = data, .pmtype = "random") %>%
pmtables::st_notes(footnotes$ci, footnotes$cv) %>%
pmtables::st_notes_str() %>%
pmtables::st_notes(footnotes$cvOmegaEq, footnotes$cvSigmaEq)