metalabr 1.0.0

MetaLab data now lives in versioned, citable releases on Redivis (https://stanford.redivis.com/datasets/81tq-8dp5ge6b9), and metalabr reads them by default. Every data-access call announces which release it used.

Data access

• get_metalab_data() now reads released data from Redivis by default, with a version argument ("current" by default, or a release name like "2023.1" to pin). The legacy live-Google-Sheets path is still available by passing dataset metadata (get_metalab_data(metadata)); it is intended for curators building releases.
• get_metalab_metadata() likewise reads the released dataset registry by default (with sheet_status/data_as_of provenance columns); passing a datasets.yaml path/URL retains the legacy behavior.
• get_current_metalab_data() now downloads the current release served by the MetaLab site instead of a snapshot committed to GitHub in 2023, and returns the effect-size data frame — like every other data-access function — with the release announced in a message and recorded in the metalab_release attribute. (metalabr 0.x instead loaded objects into the global environment, which CRAN policy disallows; use get_metalab_metadata() for what was the dataset_info object.)
• Correlation imputation no longer sets a hardcoded RNG seed: the seed is a documented argument (get_metalab_data(imputation_seed = 111), the historical default, reproducing released data exactly), and the session’s RNG state is saved and restored around the imputation.
• New get_metalab_versions() lists releases and their Redivis versions.
• New introductory vignette (vignette("metalabr")) covering released-data access and version pinning.
• All network access fails gracefully with a message (returning NULL) rather than an error.

Visualizations

• metalab_scatter_plot() was unusable outside the retired Shiny app (it referenced reactive objects); it now has a working data-in/ggplot-out interface consistent with the other plot functions.
• metalab_violin_plot() supports every effect-size type (previously it errored for anything but Hedges’ g) and handles multiple moderators.
• metalab_forest_plot() fits its model once instead of four times, and its moderator handling works outside the app.
• metalab_funnel_plot() works with moderators outside the app (it previously referenced free variables that only existed in the app environment).
• New metalab_funnel_test(): an Egger-style asymmetry test adapted to the multilevel model (√vᵢ as a fixed-effect moderator). The legacy app’s regtest() call always errored (invisibly) on multilevel models.
• Plot colors no longer require the GitHub-only langcog package.

Removed / deprecated

• viz_app() is deprecated: the interactive applications are superseded by the in-browser visualizations at https://metalab.stanford.edu. The internal Shiny app code (visualization, power analysis, validation) and the abandoned Google-Drive revision machinery were removed.

Fixed

• The package now declares and imports its dependencies correctly — library(metalabr) works without attaching dplyr first (fixes #6).
• dplyr::add_rownames() (defunct) and other retired tidyverse idioms were replaced; the pipeline runs on current tidyverse releases.
• Invalid License field replaced with MIT + file LICENSE.

Compatibility notes

• Effect-size computation is characterization-tested against the released database: the 1.0.0 pipeline reproduces the legacy pipeline’s output exactly (all effect-size branches, the hardcoded special-case studies, seed-111 correlation imputation, and derived columns).
• In released data on Redivis, the Abstract rule learning moderator column rule.type is named rule_type (Redivis does not allow dots in column names). Data frames loaded via get_current_metalab_data() keep the legacy name.

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