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Merge pull request #128 from pharmaverse/127_1_1_release
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[skip vbump] Closes #127: 1.1 release
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manciniedoardo authored Oct 25, 2024
2 parents 607d7be + 2982a47 commit 590229a
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6 changes: 3 additions & 3 deletions DESCRIPTION
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Package: pharmaversesdtm
Type: Package
Title: SDTM Test Data for the 'Pharmaverse' Family of Packages
Version: 1.0.0
Version: 1.1.0
Authors@R: c(
person("Edoardo", "Mancini", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0009-0006-4899-8641")),
person("Gayatri", "G", role = "aut"),
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Description: A set of Study Data Tabulation Model (SDTM) datasets from the Clinical
Data Interchange Standards Consortium (CDISC) pilot project used for testing
and developing Analysis Data Model (ADaM) datasets inside the pharmaverse
family of packages. SDTM dataset specifications are described in: CDISC Submission Data Standards Team
(2021) <https://www.cdisc.org/system/files/members/standard/foundational/SDTMIG%20v3.4-FINAL_2022-07-21.pdf>.
family of packages. SDTM dataset specifications are described in the CDISC SDTM implementation guide,
accessible by creating a free account on <https://www.cdisc.org/>.
Language: en-US
License: Apache License (>= 2.0)
URL: https://pharmaverse.github.io/pharmaversesdtm/, https://github.com/pharmaverse/pharmaversesdtm/
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10 changes: 6 additions & 4 deletions NEWS.md
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# pharmaversesdtm (development version)
# pharmaversesdtm 1.1.0

# New features
## New features

- Pediatrics data for anthropometric measures (`dm_peds` and `vs_peds`) was added (#88).
- Pediatrics data for anthropometric measures (`dm_peds` and `vs_peds`) was added. (#88)

- Add `CMENRTPT` to `cm`. (#120)
- `CMENRTPT` variable was added to the `cm` dataset. (#120)

- `AELOC` variable was added to the `ae_ophtha` dataset. (#110)

<details>
<summary>Developer Notes</summary>
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8 changes: 6 additions & 2 deletions data-raw/ae_ophtha.R
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## Create possible AELAT values - as collected on CRF ----
lat <- c("LEFT", "RIGHT", "BOTH")

## Create AELAT variable ----
## Create AELAT, AELOC variable ----
# Use random assignment of lat values where AESOC is "EYE DISORDERS"
# Set seed so that result stays the same for each run
set.seed(1)
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)

ae_ophtha <- ae_ophtha %>%
add_labels(AELAT = "Laterality")
mutate(AELOC = if_else(AESOC == "EYE DISORDERS", "EYE", NA_character_))

ae_ophtha <- ae_ophtha %>%
add_labels(AELAT = "Laterality") %>%
add_labels(AELOC = "Location")

# Label dataset ----
attr(ae_ophtha, "label") <- "Adverse Events"
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