Background | Deming Regression | Simple Deming Regression | Model Diagnostics | Fitted Values and Residuals | Weighted Deming Regression | Passing-Bablok Regression | When to Use Passing-Bablok | Basic Usage | Summary and Plots | Bootstrap Confidence Intervals | Joint Confidence Regions | Visualizing the Joint Confidence Region | Joint Hypothesis Test | Theoretical Details | Deming Calculative Approach | Joint Confidence Region Calculative Approach | Measurement Error | Weights | Estimating the Slope and Intercept | References

Agree or Tolerate? | Joint versus Intersection-Union (IU) Bounds | Two questions | Limits of agreement (agreement_limit()) | Tolerance limits (tolerance_limit()) | Why the defaults differ | What to report | Tolerance | Calculative Approach | Notation | Arguments Influencing the Model | The model | The bias and its standard error | Prediction interval | Upper confidence bound for the SD | Tolerance limits: bound_type = "joint" | Tolerance limits: bound_type = "iu" | Bootstrap calibration: tol_method = "boot_cal" (experimental) | Summary of the degrees of freedom | Coverage in simulations | Model assumptions | Example | Agreement | Arguments Influencing the LoA Calculations | Simple Agreement | Calculation Steps | Repeated Measures Agreement | Replicates | Calculative Steps | Nested | How to Test a Hypothesis | Checking Assumptions | An Example | Proportional Bias | Log transformation | Visualizing "Big" Data | References

Re-analysis of a Previous Study of Agreement | Concordance | Rectal Temperature | Esophageal Temperature | Tolerance Limits to Assess Agreement | References

Simple Agreement | agree_test | Calculations in for Simple Agreement | Shieh's test | Limits of Agreement | Concordance Correlation Coefficient | Repeated Measures Agreement | agree_reps | agree_nest | Calculations for agree_reps & agree_nest | agree_nest LoA | LoA | Lower LoA CI | Upper LoA CI | agree_reps LoA | CCC from U-statistics | Checking Assumptions | An Example | Proportional Bias | Non-parametric Alternatives | "Big" Data | Mixed Models | References

Introduction | Available Methods | Understanding the Approaches | Hypothesis Testing vs. Estimation | Method 1: Exact Agreement Test | Overview | Usage | Example: Sample Size Calculation | Method 2: Bland-Altman Power Curves | Example: Power Curve | Method 3: Expected Half-Width | Example: Sample Size for Precision | Method 4: Assurance Probability | Example: Sample Size with Guarantee | Decision Guide for the Method | Handling Clustered/Nested Data | The Problem | My Best Approximation: Design Effect | Understanding ICC | Application Workflow | Example: Repeated Measures Design | Impact of ICC | When Design Effect Works Well | Complete Example with Clustering | Practical Recommendations | Planning Checklist | Conservative Planning | References

Introduction to TOST | Beyond Equivalence: Minimal Effects Testing | Getting Started with Sample Data | Independent Groups Analysis | Basic Equivalence Testing | Using t_TOST | Using simple_htest | Viewing Results | Visualizing Results | 1. Simple Dot-and-Whisker Plot | 2. Consonance Density Plot | 3. Consonance Plot | 4. Null Distribution Plot | Describing Results in Plain Language | Paired Samples Analysis | Using the Sleep Data with Paired Analysis | Using Separate Vectors for Paired Data | Minimal Effect Testing (MET) | Interpreting MET Results | Warning: careful using narrow equivalence bounds | One Sample t-test | Working with Summary Statistics Only | Power Analysis for TOST | Conclusion | References

Simple Correlation Test | Advantages of z_cor_test | Using Summary Statistics | Bootstrapped Correlation Test | Robust Correlation Methods | Comparing Correlations | Summary Statistics Approach | Bootstrapped Comparison | Practical Recommendations | Advanced Usage | Custom Bootstrap Methods | Working with Missing Data | References

Introduction | The Theory Behind F-test Equivalence Testing | Practical Application with TOSTER | Setting Up | Traditional ANOVA | Equivalence Testing Using the Raw F-statistic | Interpreting the Results | Equivalence Testing Using ANOVA Objects | Minimal Effect Testing | Visualizing Partial Eta-Squared | A Second Example: Small Effect | Power Analysis for F-test Equivalence Testing | Sample Size Calculation | Power Calculation | Detectable Equivalence Bound | Choosing Appropriate Equivalence Bounds | Conclusion | References

Introduction to Robust TOST Methods | When to Use Robust TOST Methods | Wilcoxon TOST | Key Features and Usage | Interpreting the Results | Rank-Biserial Correlation | Confidence Intervals | Conversion to other effect sizes | Guidelines for Selecting Effect Size Measures | Brunner-Munzel | Overview and Advantages | Basics of the Calculative Approach | Example | Interpreting Brunner-Munzel Results | When to Use Permutation | Bootstrap TOST | Advantages of Bootstrapping | Two Sample Algorithm | Choosing the Number of Bootstrap Replications | Interpreting Bootstrap TOST Results | Ratio of Difference (Log Transformed) | Why Use The Natural Log Transformation? | Applications Beyond Bioequivalence | log_TOST | Interpreting the Means Ratio | Bootstrap + Log | Just Estimate an Effect Size | Choosing Between Different Bootstrap CI Methods | Summary Comparison of Robust TOST Methods | Conclusion | References

Three between subject conditions | Power in Repeated Measures ANOVA | Two within conditions | Power in Repeated Measures ANOVA with More than 2 Groups | The relation between Cohen's f and Cohen's d | 2x2 ANOVA, within-between design | Two-way ANOVA, between participants Design | 3x3 Between Subject ANOVA | Two by two ANOVA, within design

Introduction | One-way ANCOVA | @cohen_book Method | @shieh_ancova Method | Extending to factorial ANOVAs | ANCOVA_analytic | Example: 2x3 Design | Contrasts | References

Bias Correction (Hedges) | Independent Samples | Variances Assumed Unequal: Cohen's d(av) | Variances Assumed Equal: Cohen's d | Glass's Delta | Paired Samples | Cohen's d(z): Change Scores | Cohen's d(rm): Correlation Corrected | One Sample | Confidence Intervals | @Cousineau2021 Method (smd_ci = "goulet") | The non-central t-method (smd_ci = "nct") | Central t-method | Normal method | Just Estimate the SMD | Plotting SMDs | Comparing SMDs | Raw Data | Visualize | References

Equivalence Testing with TOSTER | Equivalence Test for Meta-analysis | Independent Groups Equivalence Test | Independent Groups Student's Equivalence Test | Independent Groups Welch's Equivalence Test | One-Sample Equivalence Test | Equivalence test for correlations

Background | Code Demonstration | Convergence Issues | Calculative Approach | Model | Components of Variance | Intraclass Correlation Coefficients | ICC Confidence Intervals | ICC(1,1) | ICC(2,1) | ICC(3,1) | ICC(1,k) | ICC(2,k) | ICC(3,k) | Standard Error Calculations | Coefficient of Variation | Other Confidence Intervals | Chi-square | Bootstrap | Inter-Rater Reliability | References

Installation | Superpower_options | ANOVA_design function | Specifying the design using 'design' | Specifying the means using 'mu' | Specifying label names | Specifying the correlation | Specifying the correlation matrix. | Specifying the sample size | Specifying the standard deviation | Simulation-Based Power Calculations | The ANOVA_power function | The ANOVA_exact function | An Example | Power in a Two Group One-Way ANOVA | Plotting Power | The plot_power function | Power-Sensitivity Relationship: Morey Plots

A note of caution | Post hoc pairwise comparisons | Customized emmeans contrasts | Equivalence and non-superiority/-inferiority tests | Joint tests

Introduction | How are error rates minimized? | Minimizing Error Rates | Balancing Error Rates | Relative costs and prior probabilities | Extending to the Analysis of Variance | An Example with ANOVA_exact2 | ANOVA_compromise