From raw clinical codes to a report-ready table | 1. Prepare readable data | 2. Start with the data, not a test | 3. Assess selected continuous variables | 4. Build Table 1 | 5. Ask a focused inferential question | What this workflow deliberately avoids

Function options at a glance | Guided interface | gtstats_app() | Choose the right table function | 1. Understand the data | describe_data() | assess_distribution() | assess_variance() | 2. Describe and compare | summary_table() | Table-building helpers | add_ci() | add_summary() (incremental builder) | Specialist and structural helpers | compare_groups() | Exact test = "auto" algorithm | effect_size() | correlation() | 3. Epidemiology | epi_table() | proportion_stats() | rate_stats() | crosstabs() | 4. Plots, inspection, and output | plot_compare() | plot_correlation() | Audit functions | customise_table() | to_gt() | to_flextable() | save_output() | The shortest useful workflow

The workflow | Install and load | 1. Understand a dataset | Built-in teaching datasets | Prefer a guided interface? | 2. Assess distribution for descriptive reporting | How Auto chooses an inferential test | 3. Create a Table 1 | 4. Compare one variable | 5. Customise and export

From raw clinical codes to a report-ready table | 1. Prepare readable data | 2. Start with the data, not a test | 3. Assess selected continuous variables | 4. Build Table 1 | 5. Ask a focused inferential question | What this workflow deliberately avoids

Citation | BibTeX | Reproducibility

Function options at a glance | Guided interface | gtstats_app() | Choose the right table function | 1. Understand the data | describe_data() | assess_distribution() | assess_variance() | 2. Describe and compare | summary_table() | Table-building helpers | add_ci() | add_summary() (incremental builder) | Specialist and structural helpers | compare_groups() | Exact test = "auto" algorithm | effect_size() | correlation() | 3. Epidemiology | epi_table() | proportion_stats() | rate_stats() | crosstabs() | 4. Plots, inspection, and output | plot_compare() | plot_correlation() | Audit functions | customise_table() | to_gt() | to_flextable() | save_output() | The shortest useful workflow

Quantify the magnitude separately | Default selection policy | Ordinal values: make the meaning explicit | Proportions are estimates, not automatically tests | Continuous outcomes | Summary-table p-values | Correlation | Rates | Inspect what was checked

The policy in one minute | Key terms | Start by describing missingness | Descriptive tables: percentage denominators | Proportions and confidence intervals | Rates use complete event-time records | Cross-tabs, comparisons, and correlations | Distribution assessment | Reporting checklist | What gtstats does not do automatically

The workflow | Install and load | 1. Understand a dataset | Built-in teaching datasets | Prefer a guided interface? | 2. Assess distribution for descriptive reporting | How Auto chooses an inferential test | 3. Create a Table 1 | 4. Compare one variable | 5. Customise and export

Introduction | A minimal table | Adding an overall column | Summary-table options at a glance | How global choices and variable exceptions work | Which layout option controls which columns? | Compact binary variables | Precision and labels | Choosing percentage denominators and missing rows | Showing the denominator in every categorical cell | Mean with a confidence interval | Adding proportion rows | Adding a total row | Adding p-values | Specifying tests manually | Paired tests | Adding rate rows | Adding custom rows | The full workflow | Styling the output | Complete customisation guide | A journal-style recipe | Relabelling without changing the analysis | A clean table without explanatory notes | Exporting to Word | Summary

Built-in teaching datasets | birthwt: real clinical teaching data | trial_data: independent groups and rates | paired_data: repeated measurements | outbreak_data: line-list outbreak analysis | surveillance_data: aggregate surveillance rates | Provenance and reuse | Transparency note

gtstats App Manual | Launch the app | Close the app safely | App dependencies | Recommended app workflow | Data tab | Data Prep tab | Uploading files | Preview and data dictionary | Reusable data code | Understand tab | Describe data | Assess distribution | Show spread by group | Code panel | Summary table tab | Choose a group | Select variables | Optional ingredients | Summary-statistic overrides | Presentation controls | Build the table layer by layer | Add p-values | Customise appearance | Preview, export, and code | Epi table tab | Customise table tab | Compare groups tab | Test control | Result and Audit panels | Correlation tab | Comparison plots | Crosstabs tab | History tab | Help tab | Saving outputs | Troubleshooting | The app does not open | Excel upload gives an error | A table or comparison is blank | A variable seems to have the wrong type | I see (blank) in a result | Chrome or a browser crashes | Best practice

Citation | BibTeX | Reproducibility

Quantify the magnitude separately | Default selection policy | Ordinal values: make the meaning explicit | Proportions are estimates, not automatically tests | Continuous outcomes | Summary-table p-values | Correlation | Rates | Inspect what was checked

The policy in one minute | Key terms | Start by describing missingness | Descriptive tables: percentage denominators | Proportions and confidence intervals | Rates use complete event-time records | Cross-tabs, comparisons, and correlations | Distribution assessment | Reporting checklist | What gtstats does not do automatically

Introduction | A minimal table | Adding an overall column | Summary-table options at a glance | How global choices and variable exceptions work | Which layout option controls which columns? | Compact binary variables | Precision and labels | Choosing percentage denominators and missing rows | Showing the denominator in every categorical cell | Mean with a confidence interval | Adding proportion rows | Adding a total row | Adding p-values | Specifying tests manually | Paired tests | Adding rate rows | Adding custom rows | The full workflow | Styling the output | Complete customisation guide | A journal-style recipe | Relabelling without changing the analysis | A clean table without explanatory notes | Exporting to Word | Summary

Built-in teaching datasets | birthwt: real clinical teaching data | trial_data: independent groups and rates | paired_data: repeated measurements | outbreak_data: line-list outbreak analysis | surveillance_data: aggregate surveillance rates | Provenance and reuse | Transparency note

gtstats App Manual | Launch the app | Close the app safely | App dependencies | Recommended app workflow | Data tab | Data Prep tab | Uploading files | Preview and data dictionary | Reusable data code | Understand tab | Describe data | Assess distribution | Show spread by group | Code panel | Summary table tab | Choose a group | Select variables | Optional ingredients | Summary-statistic overrides | Presentation controls | Build the table layer by layer | Add p-values | Customise appearance | Preview, export, and code | Epi table tab | Customise table tab | Compare groups tab | Test control | Result and Audit panels | Correlation tab | Comparison plots | Crosstabs tab | History tab | Help tab | Saving outputs | Troubleshooting | The app does not open | Excel upload gives an error | A table or comparison is blank | A variable seems to have the wrong type | I see (blank) in a result | Chrome or a browser crashes | Best practice

How rank change is calculated | What each status means | Latest, all, and explicit comparisons | Detailed labels and long names | Customise movement colours and legend text | Customise group legends in ggrank()

Let ggrank calculate the ranks | Use existing ranks without marks or values | Group colours and prepared labels | Inspect the underlying comparison | Use the graphical interface

Example Question | Logistic Outcome | Path Diagram | Quoted Names | Linear Outcome | How To Report | What Not To Claim

Which Function Should I Use? | How the Interaction Tests Differ | Identify Confounders | Mantel-Haenszel Estimate | Test Interaction | Survival Confounding and Interaction | Causal Mediation | Overlap and Difference | What To Inspect

Customize Labels | Customisation Options At A Glance | Merge Tables | Keep Binary Rows Consistent | Save Outputs | Word Reports | What To Inspect

Column Percentages | Row Percentages | Summary Choices | Output Format | What To Inspect

Convergence Screening | Collinearity Screening | Model Fit Plots | Proportional Hazards Screening | Stepwise Model Selection | Build Candidates in the App | What To Inspect

Function Options at a Glance | Common Choices | Describe and Inspect Data | descriptive_table() | dissect() | Regression Tables | uni_reg() | multi_reg() | stratified_uni_reg() | stratified_multi_reg() | Cox and Parametric Survival Regression | cox_reg() | surv_reg() | Kaplan-Meier and Survival Summaries | km_plot() | survival_summary() | survival_quantiles() | survival_prob() and km_risk_table() | logrank_test() | rmst_table() | Parametric survival helpers | Regression Plots and Model Fit | plot_reg() | plot_reg_combine() | plot_model_fit() | Forest Tables and Forest Plots | forest_df() | forest_reg() | save_forest() | Diagnostics, Selection, and Model Comparison | check_convergence() | check_collinearity() | select_models() | compare_models() | Compare Models in the gtregression App | Confounding, Interaction, and Mediation | identify_confounder() | interaction_models() | mediation_analysis() | plot_mediation() | Merge, Modify, and Export | merge_tables() | modify_table() | Save helpers | Practical Defaults

Univariable Models | Multivariable Models | Exposure-Specific Adjusted Models | Optional Model Statistics | Other Effect Measures | Cox Survival Models | Parametric Survival Models | Continuous Outcomes | What To Inspect

gtregression | What You Can Make | What Powers the Package | Install | Prepare Example Data | Five-Minute Workflow | Describe | Model | Visualise | Merge and Polish | Where To Go Next

gtregression App Manual | Launch the App | Close the App Safely | App Dependencies | Recommended Workflow | Core and Additional Options | Quick-Start Templates | Workflow Guide | Live Analysis Status and Preflight Checks | Select and Clear Variable Buttons | Data Tab | Data Prep Tab | Descriptive Tab | Binary Variables | Numeric Statistic Overrides | Regression Tab | Reference Categories | Model Statistics | Stratified Regression | Survival Tab | Kaplan-Meier Plots | Visualise & Export Tab | Model Fit | Export Size Presets | Forest Plot Controls | Download Formats | Session Code | Merge Tables | Regression Plots | Modify Table | Forest Tables | Advanced Tab | Build and Compare Candidate Models | Birth Weight Example | Cox and Parametric Survival Examples | Reading the Comparison | Model Selection and Comparison | Role Checks | Confounding and Interaction | Mediation Tab | Saving Outputs | Troubleshooting | The App Does Not Open | The Browser Preview Looks Cramped | Forest Plot X-Axis Labels Overlap | Forest Plot Columns Feel Too Narrow | Kaplan-Meier Curves Look Almost Flat | Merged Tables Do Not Align as Expected | Chrome or Browser Crashes | Nothing Appears After Clicking a Button | Beginner Case Study: Birth Weight | Best Practice

Kaplan-Meier Curve | Risk Table | Restricted Mean Survival Time | Kaplan-Meier Summary | Survival Quantiles | Survival Probabilities | Log-Rank Test | Parametric Survival Model Comparison | Parametric Survival Fit Plot | Parametric Survival Prediction | One Regression Plot | Adjusted Regression Plot | Compact Binary Predictors | Log Axis and Tick Marks | Compare Crude and Adjusted Effects | Publication-Style Forest Table | Fine-Tune Forest Tables | What To Inspect

Describe by Stratum | Univariable by Stratum | Full Multivariable Model by Stratum | Exposure-Specific Adjusted Models by Stratum | Forest Plot by Stratum | What To Inspect

1. Describe The Cohort | 2. Show Observed Survival | 3. Compare Survival Curves | 4. Fit Cox Regression | 5. Fit Parametric Survival Regression | 6. Predict Survival Probabilities | 7. Visualise And Export Model Results | Survival Workflow Map