Overview | Package Architecture | Function Structure | Software Testing | Continuous Integration | GitHub Structure | Release Checklist | Pre-release | CRAN Submission | Post-release | Contributing

Workflow | 1. Understand the theoretical background of SPRTs | 2. When to use SPRTs | 3. Plan your resources | 4. Plan the data collection and register your test specifications | 5. Collect the data and apply the SPRTs | 5. Reporting of the results | References

Why Sample Size Planning Matters | Resource Constraints and Decision Rates | The plan_sample_size() Function | Pre-computed Simulation Database | Getting Started | Your First Sample Size Report | Function Parameters | Input Validation | Practical Use Cases | Case 1: Comparing Different Effect Sizes | Case 2: Saving Reports to a Specific Location | Case 3: Preparing Multiple Scenarios | Managing the Simulation Data

Hypotheses | The $F$ Statistic | The Likelihood Ratio | Decision Boundaries | Decision Rule | Efficiency and Robustness | How to use seq_anova() | Step 1: Simulate or Load Data | Step 2: Initial Sequential Analysis | Step 3: Repeated Sequential Testing | Step 4: Final Analysis | How to plot the ANOVA results | Scenario 1: Balanced Data with Perfect Sampling Order | Scenario 2: Unbalanced Data with Imperfect Sampling Order | References

What is the sequential t-test? | How do I use the seq_ttest() function? | x argument: formula input | Two-sample test | One-sample test | x argument: numeric input | Further arguments | Paired | Alternative | Na.rm | Verbose | How do I get access to the results? | References

The Sequential Testing Principle | The Likelihood Ratio and Decision Boundaries | Random Sample Size | Why SPRTs Always Stop | Efficiency | The Bias-Efficiency Tradeoff | Practical Considerations | References

Use Case | Hypothesis | Data Analysis | Report Results | References