bayprior 0.2.2

UX improvements

  • Three-state auto theme — theme now cycles Auto → Dark → Light on toggle. In Auto mode the app follows the OS prefers-color-scheme setting, which most operating systems tie to time of day. The button label shows the active state and whether it is following the OS or set manually (e.g. Auto (dark), Dark (manual)). Switching back to Auto removes the stored preference and resumes OS tracking.

  • Disabled downstream buttons — analysis buttons (Run Diagnostics, Run Sensitivity Analysis, Build robust/sceptical/power prior, Compute consensus prior) are now greyed out with a not-allowed cursor when no prior has been fitted. Hovering shows the tooltip “Fit a prior in Prior Elicitation first”. Buttons re-enable immediately when a prior is fitted. The Mahalanobis Conflict Setup button is intentionally excluded as it does not require an elicited prior.

  • Prior summary card in sidebar — the active prior badge now shows a mini stats table with Mean, SD, and 95% CrI (where available) below the distribution family and label. Updates reactively on every prior change. Mixture priors show Mean and SD only (no closed-form CrI).

  • Diagnostic tooltips — each conflict value box (Box p-value, Surprise index, Overlap coefficient) now has an info icon that displays a plain- language explanation on hover, useful for non-statistician stakeholders.

Bug fixes

  • Accepted updated plot snapshots for plot_tornado() and plot_sensitivity() following the axis label formatting change in v0.2.1 (snake_case -> title case).

Documentation

  • Sensitivity plot labels updated in plot_tornado() and plot_sensitivity() package functions directly (not just the Shiny layer), so label formatting applies when functions are called from R as well as in the app.

bayprior 0.2.1

UX improvements

  • Welcome tab now shows an SVG workflow diagram of all six analytical steps with colour-coded boxes and arrows.
  • Sidebar menu items now show a green glowing dot when each step is complete (elicitation, pooling, conflict, sensitivity, robust priors).
  • Export Report compliance checklist is now fully reactive — items update live with colour-coded icons (green check, amber minus, red X) and a ready/not- ready summary alert.
  • Package version (bayprior vX.X.X) now displayed in the sidebar footer.

Deployment fixes

  • Removed pkgload::load_all() from app.R — it was a development-only line that caused startup failure on shinyapps.io.
  • Added renv::snapshot(type = "explicit") to deployment workflow to prevent dev tools (pkgload, pkgbuild, callr, desc) from entering renv.lock.

Documentation

  • Information boxes on Welcome tab updated: Distributions 4 → 6, Conflict diagnostics → Data types (Binary · Continuous · Poisson · Survival).

bayprior 0.2.0

New features

  • Added elicit_exponential() — elicits an Exponential(rate) prior for constant hazard rates and Poisson rate priors. Supports "moments" (mean to rate), "rate" (direct), and "quantile" (1D optimisation) methods. The Exponential distribution is conjugate for Poisson and survival data via Gamma-Poisson/Exponential updating.

  • Added elicit_weibull() — elicits a Weibull(shape, scale) prior for non-constant hazard survival times (OS, PFS). Supports "moments" (2D Nelder-Mead), "params" (direct shape and scale), and "quantile" (2D Nelder-Mead) methods. Posteriors are approximated via Normal matching.

  • Added "poisson" data type to prior_conflict(), sensitivity_grid(), and sensitivity_cri(). Supports count/adverse-event-rate endpoints: list(type = "poisson", x = 12, n = 100) (events / person-time). Conjugate update: Gamma(shape + x, rate + n).

  • Added "survival" data type to prior_conflict(), sensitivity_grid(), and sensitivity_cri(). Supports OS/PFS hazard rate endpoints: list(type = "survival", x = 20, n = 400) (events / total follow-up time). Conjugate update: Gamma(shape + x, rate + n) (Gamma-Exponential).

  • Added density and x-range support for Exponential and Weibull distributions in plot.bayprior(). Previously these distributions rendered blank density plots; they now display correctly.

  • Added comprehensive validation layer across all modules:

    • .check_prior_data_compat() — warns when a prior family is atypical for the chosen data type (e.g. Beta prior + Poisson data).
    • .check_pooling_compat() — blocks pooling of distributions with incompatible supports (e.g. Beta + Normal); warns for same-support cross-family pooling (e.g. Gamma + Exponential).
    • .check_sensitivity_compat() — warns for single-parameter families (Exponential) and cross-family mixtures; blocks incompatible-support mixture sensitivity.
    • .validation_alert() — renders Bootstrap alert boxes for inline UI feedback in the Shiny app.

  • Sensitivity analysis is now fully independent of conflict diagnostics. The Sensitivity Analysis module has its own data entry UI (data type selector, events/n for binary, mean/SD/n for continuous, events/exposure for Poisson, events/follow-up for survival) that auto-populates the correct type from the active prior family. Previously, running conflict diagnostics was required before sensitivity analysis could proceed.

  • All Shiny modules now reset outputs automatically on input change, preventing stale results from being displayed alongside new inputs. Each module uses observeEvent(list(...)) watching all its relevant inputs to reset result reactives immediately. The active prior sidebar indicator is preserved during elicitation input changes (only the density plot and parameter table reset; shared$current_prior is retained until a new prior is explicitly fitted).

Bug fixes

  • Fixed prior_report() producing blank figures in Word (.docx) reports. knitr was writing absolute figure paths to the markdown; pandoc could not resolve them. Fixed by using fig.path = "figures/" (relative) with base.dir = tmp_dir for docx/pdf, and knitr::image_uri for HTML.

  • Fixed prior_report() failing for PDF with “tikzfill.image.sty not found”. Added tinytex::tlmgr_install() recommendation in documentation. The default-image-extension: pdf Quarto default is now overridden to png via YAML injection in the pre-executed markdown.

  • Fixed mixture prior hyperparameters section in prior_report.qmd rendering as literal markdown (## Hyperparameters not available) rather than as formatted text. Added #| results: asis to the fitted-params chunk and updated to show a component summary table for mixture priors.

  • Fixed mod_conflict_mahal.R containing a stale duplicate definition of mod_conflict_ui that was overriding the correct 4-choice version in mod_conflict.R (files sourced alphabetically, mahal comes after conflict). Removed the duplicate; mod_conflict_mahal.R now only contains mod_mahal_ui and mod_mahal_server.

Documentation

  • Updated bayprior-package.R to document all six distribution families, all four data types for conflict diagnostics and sensitivity, and the new validation functions.
  • Updated all six vignettes to cover Exponential and Weibull elicitation, Poisson and survival conflict diagnostics, independent sensitivity data entry, and the output reset behaviour.
  • Updated README with new badges, six-family distribution table, four-data-type conflict table, and updated Quick Start examples.

bayprior 0.1.2

Bug fixes

  • Fixed prior_report() failing on remote platforms (shinyapps.io, Posit Connect) due to Quarto spawning a subprocess that could not find the bayprior package. The report now uses a two-step approach: knitr::knit() executes all R code in the current session, then quarto::quarto_render(execute = FALSE) handles formatting via pandoc only. No R subprocess is spawned in the second step (#1).

  • Fixed mod_sensitivity: sensitivity analysis no longer requires conflict diagnostics to have been run first. The module now has its own data entry UI (data type, events/n for binary; mean/SD/n for continuous) that auto-selects the correct type based on the prior family (Beta → binary, others → continuous). Previously the fallback always used type = "continuous", causing conjugate updating to fail for Beta priors and returning NA for all grid evaluations.

  • Fixed “Using data from Conflict Diagnostics” label appearing even when no conflict diagnostics had been run. The label is now generated inside renderUI conditionally on shared$conflict.

  • Fixed non-ASCII characters (─, —) in R/app_ui.R causing an R CMD check WARNING. All box-drawing and em-dash characters replaced with ASCII equivalents.

  • Fixed prior_report() missing @param documentation for prior_plot, overlay_plot, tornado_plot, and heatmap_plot, causing an R CMD check WARNING about undocumented arguments.

New features

  • Added robust_prior, sceptical_prior, power_prior, robust_plot, sceptical_plot, and power_plot arguments to prior_report(). When supplied, robust and sensitivity priors appear as a dedicated section in the report with parameter tables and density plots. The compliance checklist row “Robust / sceptical prior computed” is automatically marked Complete.

  • Added bayprior hex logo to the Shiny app header and browser favicon. Logo is served from inst/app/www/favicon.png.

bayprior 0.1.1

Initial release

Prior Elicitation

  • Quantile matching, moment matching, and SHELF roulette for Beta, Normal, Gamma, and Log-Normal families
  • elicit_beta(), elicit_normal(), elicit_gamma(), elicit_lognormal(), elicit_roulette(), elicit_mixture()

Expert Pooling

  • Linear and logarithmic pooling with Bhattacharyya agreement diagnostics
  • aggregate_experts()

Conflict Diagnostics

  • Box p-value, surprise index, KL divergence, Bhattacharyya overlap
  • Multivariate Mahalanobis distance for co-primary endpoints
  • prior_conflict(), conflict_mahalanobis()

Sensitivity Analysis

  • Posterior quantity grid and credible interval sensitivity with tornado plots and influence heatmaps
  • sensitivity_grid(), sensitivity_cri()

Robust Priors

  • Robust mixture prior (Schmidli et al., 2014): robust_prior()
  • Sceptical prior (Spiegelhalter & Freedman, 1994): sceptical_prior()
  • Calibrated power prior (Ibrahim & Chen, 2000): calibrate_power_prior()

Reporting

  • HTML, PDF, and Word prior justification reports via Quarto: prior_report()
  • FDA/EMA regulatory compliance checklist

Documentation

  • Added Quarto GitHub Pages documentation site at https://ndohpenngit.github.io/bayprior/ with six rendered vignettes, a Changelog page, and a Cheat Sheet. Site auto-rebuilds on every push to main via GitHub Actions.

  • Updated all six vignettes to document new prior_report() arguments, the sensitivity analysis CrI toggle, and the robust priors report integration.

  • Updated README.md with live app badge, and Documentation section linking to the GitHub Pages site.

App

  • Full interactive Shiny application: run_app()
  • Dark/light mode toggle with localStorage persistence
  • bayprior hex logo in header and browser tab