Cards | Value & info boxes | Tab box | Sidebar navigation | Header dropdown menus | Reactive outputs and renderers | Accordion, badges, buttons, icons | Toasts

Minimal dashboard skeleton | Run the app | Programmatic tab navigation | Migrating from shinydashboard | Function-name parity | Behavioural differences to know about | Removed shinydashboard parameters | Accepted, but implemented differently | Silently ignored — use these instead | Colour name mapping | Argument-ordering note

The default theme | Overriding theme variables | Adding custom SCSS | Switching the Bootswatch preset | Real-time theming | Dynamic theming

Cards | Value & info boxes | Tab box | Sidebar navigation | Header dropdown menus | Reactive outputs and renderers | Accordion, badges, buttons, icons | Toasts

Minimal dashboard skeleton | Run the app | Programmatic tab navigation | Migrating from shinydashboard | Function-name parity | Behavioural differences to know about | Removed shinydashboard parameters | Accepted, but implemented differently | Silently ignored — use these instead | Colour name mapping | Argument-ordering note

The default theme | Overriding theme variables | Adding custom SCSS | Switching the Bootswatch preset | Real-time theming | Dynamic theming

Introduction | Example use-case: Dual combination trial with historical information | Setting up the trial design | Drug info | Dose info | Initializing a blrm_trial | Specifying the prior and fitting the model | Summary of prior specification | Summary of posterior | Posterior accuracy of EWOC estimation | Posterior predictive summaries | Updating the model with new data | Data scenarios | Continuation of example: Using concurrent data | References | Session Info

Introduction | Application background | Historical data | Derivation of MAP priors | Drug A model | Drug B model | Extraction of MAP priors | MCMC samples | Mixture approximation | Combination model with MAP priors for the new study | Robustification | Equivalence of MAP and MAC (advanced) | Appendix: Model specification | Combination BLRM (new study model) | Prior specification | Meta-analytic models for the historical data | Hierarchical model for combined data (MAC) | References | Session Info

Introduction | High-level design | Supported dataset types | End-to-end example | Step 1: Auto-generate a configuration file | Step 2: Review and edit the configuration | Step 3: Simulate the study | Writing the YAML configuration manually | Granular control: glimpse and simulate individually | Splitting glimpse from simulate | Privacy protection | Limitations | Disclaimer

What is monitOS? | Core parameters | Installation | Scenario 1 — Standard trial: Follicular Lymphoma | Clinical context | Interpreting the output | Scenario 2 — Edge case: CLL Maintenance with Unequal Randomisation | Key observations for the edge case | Quick reference

Try monitOS in your browser | About Shinylive | Local Shiny App

Overview | Required Packages | Traceability: annotating and saving plots and tables | Annotating figures | Graphics helpers | xgx theme | Confidence intervals | Nonlinear smoothing (e.g. Emax), and ordinal response smoothing | Nice log scale | Reverse log transform | Nice scale for percent change data | Scaling x-axis as a time scale