rcprd: Extraction and Management of Clinical Practice Research Datalink Data

Simplify the process of extracting and processing Clinical Practice Research Datalink (CPRD) data in order to build datasets ready for statistical analysis. This process is difficult in 'R', as the raw data is very large and cannot be read into the R workspace. 'rcprd' utilises 'RSQLite' to create 'SQLite' databases which are stored on the hard disk. These are then queried to extract the required information for a cohort of interest, and create datasets ready for statistical analysis. The processes follow closely that from the 'rEHR' package, see Springate et al., (2017) <doi:10.1371/journal.pone.0171784>.

Version:	0.0.1
Depends:	data.table
Imports:	dplyr, fastmatch, RSQLite, stringr
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2024-11-13
DOI:	10.32614/CRAN.package.rcprd
Author:	Alexander Pate [aut, cre, cph]
Maintainer:	Alexander Pate <alexander.pate at manchester.ac.uk>
License:	MIT + file LICENSE
URL:	https://alexpate30.github.io/rcprd/
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	rcprd results

Documentation:

Reference manual:	rcprd.pdf
Vignettes:	Details-on-algorithms-for-extracting-specific-variables (source, R code) rcprd (source, R code)

Downloads:

Package source:	rcprd_0.0.1.tar.gz
Windows binaries:	r-devel: rcprd_0.0.1.zip, r-release: rcprd_0.0.1.zip, r-oldrel: rcprd_0.0.1.zip
macOS binaries:	r-release (arm64): rcprd_0.0.1.tgz, r-oldrel (arm64): rcprd_0.0.1.tgz, r-release (x86_64): rcprd_0.0.1.tgz, r-oldrel (x86_64): rcprd_0.0.1.tgz

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