Simulated cohort | Multiple predictors from one model | Same predictor across progressive adjustment models | Same predictor across multiple outcomes | Dose-response (exposure categories) | Marginal effects: g-computation | Marginal effects: inverse probability weighting (IPW) | Time-varying exposures and longitudinal studies | Distributed lag models | Life-course analysis: same exposure across developmental periods | Life-course analysis: comparing stages side by side (dodge) | Saving plots

Simulated data | Basic meta-analysis forest plot | Adding text columns | Subgroup analyses by region | Structured subgroup analysis with section headers | Multiple exposures: comparing PM~2.5~, NO~2~, and noise | Saving plots

Design principles | Source files | Starting data | Step 1b — Section expansion via build_sections() | Subsection expansion | Step 3 — Row type classification | Step 8 — Dodge layout | Colour assignment | Section-level text column annotations | Reference-category rows | Summary (diamond) rows | Theme system

Basic forest plot | Section headers from a grouping column | Two-level hierarchy with subsection | Adding a summary (pooled) estimate | Group colouring | Multiple estimates per row (dodge) | Wide-format text columns alongside dodged CIs | Point shapes | Adding text columns | Section-level annotations in text columns | Alternating row stripes | Themes | Saving plots

Introduction | Installation | Basic Usage | Fetching Researcher Information | Employment and Education History | Research Outputs | Professional Activities | Efficient Data Retrieval | Fetching Complete Records | Getting All Activities in One Call | Batch Processing Multiple ORCIDs | Searching the ORCID Registry | Basic Search | Advanced Search with Solr Queries | Search by DOI | Data Analysis Examples | Publication Trends Over Time | Collaboration Networks | Funding Analysis | Authentication (Optional) | When You Need Authentication | Setting Up Authentication (If Needed) | Using Authentication | API Status and Error Handling | Checking API Health | Handling Errors | Best Practices | Rate Limiting | Caching Results | Working with data.table | Additional Resources | Summary