Package: CohortSymmetry 0.2.4

Xihang Chen

CohortSymmetry: Sequence Symmetry Analysis Using the Observational Medical Outcomes Partnership Common Data Model

Calculating crude sequence ratio, adjusted sequence ratio and confidence intervals using data mapped to the Observational Medical Outcomes Partnership Common Data Model.

Authors:Xihang Chen [aut, cre], Tyman Stanford [aut], Berta Raventós [aut], Nicole Pratt [aut], Ed Burn [aut], Marti Català [aut], Danielle Newby [aut], Núria Mercadé-Besora [aut], Mike Du [aut], Yuchen Guo [aut], Kim Lopez [aut], Marta Alcalde-Herraiz [aut]

CohortSymmetry_0.2.4.tar.gz
CohortSymmetry_0.2.4.zip(r-4.7)CohortSymmetry_0.2.4.zip(r-4.6)CohortSymmetry_0.2.4.zip(r-4.5)
CohortSymmetry_0.2.4.tgz(r-4.6-any)CohortSymmetry_0.2.4.tgz(r-4.5-any)
CohortSymmetry_0.2.4.tar.gz(r-4.7-any)CohortSymmetry_0.2.4.tar.gz(r-4.6-any)
CohortSymmetry_0.2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CohortSymmetry/json (API)

# Install 'CohortSymmetry' in R:
install.packages('CohortSymmetry', repos = c('https://ohdsi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ohdsi/cohortsymmetry/issues

Pkgdown/docs site:https://ohdsi.github.io

On CRAN:

Conda:

6.43 score 2 stars 74 scripts 318 downloads 8 exports 51 dependencies

Last updated from:4691b6edd4. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK258
source / vignettesOK306
linux-release-x86_64OK239
macos-release-arm64OK1259
macos-oldrel-arm64OK1411
windows-develOK2974
windows-releaseOK2910
windows-oldrelOK2976
wasm-releaseOK141

Exports:generateSequenceCohortSetmockCohortSymmetryplotSequenceRatiosplotTemporalSymmetrysummariseSequenceRatiossummariseTemporalSymmetrytableSequenceRatiostableTemporalSymmetry

Dependencies:askpassbackportsbitbit64blobCDMConnectorcheckmateclicliprclockCodelistGeneratorcpp11crayoncurlDBIdbplyrdplyrDrugUtilisationgenericsglueherehmshttr2jsonlitelifecyclemagrittromopgenericsopensslPatientProfilespillarpkgconfigprettyunitsprogresspurrrR6rappdirsreadrrlangrprojrootsnakecasestringistringrsystibbletidyrtidyselecttzdbutf8vctrsvroomwithr

Step 1. Generate a sequence cohort
Introduction | Create a cdm object | Instantiate two cohorts in the cdm reference | Generate a sequence cohort | No specific requirements | Important Observations | Specified study period | Specified study period and prior history requirement | Specified study period, prior history requirement and washout period | Specified study period, prior history requirement and combination window | Specified study period, prior history requirement and index marker gap
Rendered froma02_Generate_a_sequence_cohort.Rmdusingknitr::rmarkdown

Last update: 2025-02-28
Started: 2024-10-15

Step 2. Obtain the sequence ratios
Introduction | Obtain sequence ratios
Rendered froma03_Summarise_sequence_ratios.Rmdusingknitr::rmarkdown

Last update: 2025-02-28
Started: 2024-05-28

Step 3. Visualise the sequence ratios
Introduction | Table output of the sequence ratio results | Modify type | Plot output of the sequence ratio results | Modify onlyASR and colours
Rendered froma04_Visualise_sequence_ratios.Rmdusingknitr::rmarkdown

Last update: 2025-02-28
Started: 2024-05-28

Step 4: Obtain aggregated data on temporal symmetry
Introduction | Obtaining temporal symmetry | Modify the cohort based on cohort_definition_id | Modify timescale
Rendered froma05_Summarise_temporal_symmetry.Rmdusingknitr::rmarkdown

Last update: 2025-02-28
Started: 2024-05-28

Step 5: Visualise temporal symmetry
Introduction
Rendered froma06_Visualise_temporal_symmetry.Rmdusingknitr::rmarkdown

Last update: 2025-02-28
Started: 2024-05-28

Introduction to CohortSymmetry
As a diagram
Rendered froma01_Introduction.Rmdusingknitr::rmarkdown

Last update: 2024-11-29
Started: 2024-04-22