knitr::opts_chunk$set( comment = "#>", collapse = TRUE, out.width = "100%", dpi = 150, eval = TRUE )
library(metalite) library(metalite.sl)
metalite.sl R package designed for the analysis & reporting of subject-level analysis in clinical trials. It operates on ADaM datasets and adheres to the metalite structure. The package encompasses the following components:
Baseline Characteristics.
This R package offers a comprehensive software development lifecycle (SDLC) solution, encompassing activities such as definition, development, validation, and finalization of the analysis.
The overall workflow includes the following steps:
prepare_*()
functions.extend_*()
functions (optional).format_*()
functions.tlf_*()
functions.For instance, we can illustrate the creation of a straightforward Baseline characteristic table as shown below.
meta_sl_example() |> prepare_base_char( population = "apat", analysis = "base_char", parameter = "age;gender" ) |> format_base_char() |> rtf_base_char( source = "Source: [CDISCpilot: adam-adsl]", path_outdata = tempfile(fileext = ".Rdata"), path_outtable = tempfile(fileext = ".rtf") )
knitr::include_graphics("pdf/base0char.pdf")
An example for interactive baseline characteristic table:
react_base_char( metadata_sl = meta_sl_example(), metadata_ae = metalite.ae::meta_ae_example(), population = "apat", observation = "wk12", display_total = TRUE, sl_parameter = "age;race", ae_subgroup = c("age", "race"), ae_specific = "rel", width = 1200 )
Additional examples and tutorials can be found on the package website, offering further guidance and illustrations.
To implement the workflow in metalite.sl, it is necessary to establish
a metadata structure using the metalite R package.
For detailed instructions, please consult the
metalite tutorial
and refer to the source code of the function
meta_sl_example()
.
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