1. Study Design & Effect Measure Alignment | 2. Multivariable GLMs with regtab() | 2.1 Logistic Regression & Robust Sandwich Covariance | Robust Standard Errors: | 2.2 Multi-Outcome Regression | 2.3 Model Extraction & Multicollinearity Diagnostics | 3. Sparse Data & Firth Penalized Likelihood Regression | 4. Time-to-Event Survival Analysis with survtab() | 4.1 Proportional Hazards Diagnostics & Advisory Audit | 4.2 Forest Plot Visualization & Methods Generation

1. The Declarative SimtablR Grammar | 1.1 Building an Inert Specification (simtab_spec) | 1.2 Plan Validation & Evaluation | 1.3 Verb Closure: Modifying Existing Results | 2. Composite Manuscript Reports with simtablr() | 3. Reviewer Analyses, Sensitivity, and Bias Auditing | 3.1 Sensitivity Analysis with sensitivity() | 3.2 Unmeasured Confounding: E-Value Analysis | 3.3 Methodological Advice and Decision Audit | 3.4 Participant Flow and Flowchart Visualization | 3.5 Reporting Checklists and Codebooks | 4. Publication Rendering, Journal Styling, and File Export | 4.1 Journal Presets | 4.2 Interactive Tables (gt) and Office Tables (flextable) | 4.3 Native Export to Word and Excel | 4.4 Automated Methodology Prose

1. Multi-Variable Baseline Cohort Description with table1() | Key Statistical Behaviors of table1() | Adding Standardized Mean Differences (SMD) via Verb Closure | 2. Focused Bivariate Analyses with tb() | 2.1 Study Design Resolution: Prevalence Ratio at Presentation, Risk Ratio in Follow-up | 2.2 Flags for quick coding | 3. Stratified Analysis & Mantel-Haenszel Pooling | 4. Stacking Multiple Bivariate Tables with rbind()

1. Defining the Diagnostic Cohort | 2. Binary Diagnostic Test Accuracy with diag_test() | Key Metrics Computed: | 2.1 Confusion Matrix Visualization | 2.2 Tidy Metric Extraction | 3. Continuous Biomarker Discrimination with roc() | 3.1 Empirical AUC and DeLong Confidence Intervals | 3.2 Threshold Optimization with Youden's J | 3.3 Publication ROC Plot | 4. Reporting Guidelines: STARD Checklist & Automated Methods