Creating plots | Customizing plots | Summarizing confounder control | Combining with forest plots | Using control quality as an analytic category | Visualizing non-confounders
Package: metaconfoundr 0.1.2.9000
metaconfoundr: Visualize 'Confounder' Control in Meta-Analyses
Visualize 'confounder' control in meta-analysis. 'metaconfoundr' is an approach to evaluating bias in studies used in meta-analyses based on the causal inference framework. Study groups create a causal diagram displaying their assumptions about the scientific question. From this, they develop a list of important 'confounders'. Then, they evaluate whether studies controlled for these variables well. 'metaconfoundr' is a toolkit to facilitate this process and visualize the results as heat maps, traffic light plots, and more.
Authors:
metaconfoundr_0.1.2.9000.tar.gz
metaconfoundr_0.1.2.9000.zip(r-4.7)metaconfoundr_0.1.2.9000.zip(r-4.6)metaconfoundr_0.1.2.9000.zip(r-4.5)
metaconfoundr_0.1.2.9000.tgz(r-4.6-any)metaconfoundr_0.1.2.9000.tgz(r-4.5-any)
metaconfoundr_0.1.2.9000.tar.gz(r-4.7-any)metaconfoundr_0.1.2.9000.tar.gz(r-4.6-any)
metaconfoundr_0.1.2.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
metaconfoundr/json (API)
| # Install 'metaconfoundr' in R: |
| install.packages('metaconfoundr', repos = c('https://malcolmbarrett.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/malcolmbarrett/metaconfoundr/issues
Datasets:
- ipi - IPI data
- ipi_metaanalysis - IPI data
- ipi_wide - IPI data
Last updated from:3af7bc98a7. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 171 | ||
| source / vignettes | OK | 195 | ||
| linux-release-x86_64 | OK | 156 | ||
| macos-release-arm64 | OK | 135 | ||
| macos-oldrel-arm64 | OK | 202 | ||
| windows-devel | OK | 109 | ||
| windows-release | OK | 105 | ||
| windows-oldrel | OK | 98 | ||
| wasm-release | OK | 156 |
Exports:%>%containscount_non_confoundersends_witheverythingfacet_constructsgeom_cochranelabel_robinslast_collaunch_metaconfoundr_appmatchesmc_detect_layoutmc_heatmapmc_longermc_study_valuesmc_trafficlightmc_widermetaconfoundrnum_rangeone_ofplot_non_confoundersscale_color_cochranescale_fill_cochranescale_shape_cochranescore_controlstarts_withsummarize_control_qualitytheme_mc
Dependencies:base64encbslibcachemclicommonmarkcpp11digestdplyrfarverfastmapfontawesomeforcatsfsgenericsggplot2gluegtablehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlifecyclemagrittrmemoisemimeotelpillarpkgconfigpromisespurrrR6rappdirsRColorBrewerRcpprlangS7sassscalesshinysourcetoolsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxtable
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Count and plot non-confounders | count_non_confounders plot_non_confounders |
| Facet by constructs | facet_constructs |
| Add Cochrane-style symbols to heatmaps and traffic light plots | geom_cochrane |
| IPI data | ipi ipi_data ipi_metaanalysis ipi_wide |
| Label values using ROBINS approach | label_robins |
| Launch metaconfoundr Shiny app | launch_metaconfoundr_app |
| Tidy metaconfoundr data layouts | mc_detect_layout mc_longer mc_study_values mc_wider |
| Plot a heatmap or traffic light plot of 'metaconfoundr()' summaries | mc_heatmap mc_trafficlight |
| Prepare a meta-analysis data set for metaconfoundr | metaconfoundr metaconfoundr() |
| Add Cochrane-style palettes to ggplots | scale_color_cochrane scale_fill_cochrane scale_shape_cochrane |
| Add a score of confounding control | score_control |
| Summarize the control quality of studies | summarize_control_quality |
| A minimal theme for metaconfoundr plots | theme_mc |
