Package: triangulate 0.0.2

Chin Yang Shapland

triangulate: Useful functions for performing evidence triangulation

What the package does (one paragraph).

Authors:Luke McGuinness [aut], Tassia Jones [aut], Chin Yang Shapland [aut, cre]

triangulate_0.0.2.tar.gz
triangulate_0.0.2.zip(r-4.7)triangulate_0.0.2.zip(r-4.6)triangulate_0.0.2.zip(r-4.5)
triangulate_0.0.2.tgz(r-4.6-any)triangulate_0.0.2.tgz(r-4.5-any)
triangulate_0.0.2.tar.gz(r-4.7-any)triangulate_0.0.2.tar.gz(r-4.6-any)
triangulate_0.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
triangulate/json (API)

# Install 'triangulate' in R:

install.packages('triangulate', repos = c('https://mrcieu.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mcguinlu/triangulate/issues

Datasets:

beta_carotene_data - Beta-carotene RoB Judgments (Raw) Domain-level risk of bias judgments for 15 studies of beta-carotene and cardiovascular outcomes.
dat_bias - Example risk of bias assessments
dat_bias_values - Example priors for the bias adjustment
dat_ind - Example indirectness assessments
dat_ind_values - Example priors for indirectness adjustment

On CRAN:

5.03 score 4 stars 10 scripts 14 exports 65 dependencies

Last updated from:9c198ec995. Checks:9 OK. Indexed: yes.

Target	Result	Time	Files	Syslog
linux-devel-x86_64	OK	152
source / vignettes	OK	196
linux-release-x86_64	OK	151
macos-release-arm64	OK	130
macos-oldrel-arm64	OK	86
windows-devel	OK	105
windows-release	OK	146
windows-oldrel	OK	101
wasm-release	OK	118

Exports:%>%interactive_bias_plot tri_absolute_direction tri_absolute_direction_invert tri_absolute_direction_quick tri_append_bias tri_append_indirect tri_calculate_adjusted_estimates tri_dat_check tri_plot_bias_direction tri_prep_data tri_swap_effect_direction tri_to_long tri_to_wide

Dependencies:base64enc bslib cachem cli commonmark cpp11 digest dplyr farver fastmap fontawesome fs generics ggplot2 glue gtable hms htmltools httpuv isoband janitor jquerylib jsonlite labeling later lattice lifecycle lubridate magrittr mathjaxr Matrix memoise metadat metafor mime nlme numDeriv otel pbapply pillar pkgconfig promises purrr R6 rappdirs RColorBrewer Rcpp rlang S7 sass scales shiny snakecase sourcetools stringi stringr tibble tidyr tidyselect timechange utf8 vctrs viridisLite withr xtable

Triangulation example: Beta-carotene and CHD

Introduction | 1. Load CHD Dataset | 2. Merge with RoB Assessments | 3. Format & Validate Input | 4. Add Indirectness & Adjust Effect Estimate for It | 5. Apply Bias Priors & Estimate Adjusted Effects | 5.1 Define Custom Priors | 5.2 Append priors and prepare data, and estimate adjusted effects | 6. Final data adjusted for both bias and indirectness | 7. Generate Bias-Adjusted Plot

Rendered frombeta-carotene-chd-example.Rmdusingknitr::rmarkdown

Last update: 2026-01-16
Started: 2025-11-27

Absolute direction of bias/indirectness

Absolute directions of bias/indirectness | Point estimate below NULL | Point estimate above NULL - Bias towards the NULL | Adding the adjustment values | Example | Additive - Favours comparator - right - positive sign | Additive - Favours intervention - left - negative sign | Proportional - Point estimate above NULL - Towards the NULL - left - negative sign | Proportional - Point estimate below NULL - Away from NULL - right - positive sign | Proportional - Point estimate below NULL - Towards the NULL - right - positive sign | Proportional - Point estimate below NULL - Away from NULL - left - negative sign

Rendered fromabsolute_direction.Rmdusingknitr::rmarkdown

Last update: 2025-11-27
Started: 2025-11-27

Adding additional levels of bias and indirectness

Rendered fromadditional-levels-of-bias-and-indirectness.Rmdusingknitr::rmarkdown

Last update: 2025-11-27
Started: 2025-11-27

Creating triangulation datasets

Introduction | Step 1: Create the example dataset | Step 2: Convert to long format | Step 3: Add absolute direction | Step 4: Append bias priors

Rendered fromCreating-triangulation-datasets.Rmdusingknitr::rmarkdown

Last update: 2025-11-27
Started: 2025-11-27

Interactive Sensitivity Analysis

Introduction | Example Data | Launch Interactive App | Conclusion

Rendered frominteractive-sensitivity.Rmdusingknitr::rmarkdown

Last update: 2025-11-27
Started: 2025-11-27

Sensitivity Analyses in Triangulate

Introduction | Create example dataset | Define Default Bias and Indirectness Priors | Run bias adjustment | Stricter sensitivity scenario | Compare results | Conclusion

Rendered fromsensitivity-analysis.Rmdusingknitr::rmarkdown

Last update: 2025-11-27
Started: 2025-11-27

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Beta-carotene RoB Judgments (Raw) Domain-level risk of bias judgments for 15 studies of beta-carotene and cardiovascular outcomes.	beta_carotene_data
Example risk of bias assessments	dat_bias
Example priors for the bias adjustment	dat_bias_values
Example indirectness assessments	dat_ind
Example priors for indirectness adjustment	dat_ind_values
Interactive bias-adjusted plot (horizontal layout)	interactive_bias_plot
Convert to absolute direction of bias or indirectness	tri_absolute_direction
Convert absolute direction back to qualitative tool labels	tri_absolute_direction_invert
Quick wrapper to apply absolute direction transformation	tri_absolute_direction_quick
Append bias priors to bias dataset	tri_append_bias
Append indirectness priors to dataset	tri_append_indirect
Calculate Bias-Adjusted Estimates	tri_calculate_adjusted_estimates
Check that required columns are present	tri_dat_check
Plot bias-adjusted and unadjusted estimates with RoB	tri_plot_bias_direction
Prepare bias and indirectness data for adjustment	tri_prep_data
Standardise Effect Direction and Adjust Bias Directions	tri_swap_effect_direction
Convert data from wide to long format	tri_to_long
Convert data from long to wide format	tri_to_wide

Usage by other packages (reverse dependencies)