East 6 User Manual
User Manual:
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- Preface
- Volume 1: The East System
- Chapter 1: Introduction to Volume 1
- Chapter 2: Installing East 6
- Chapter 3: Getting Started
- 3.1: Workflow in East
- 3.2: A Quick Overview of User Interface
- 3.3: Home Menu
- 3.4: Data Editor Menu
- 3.5: Analysis Menu
- 3.6: Design Menu
- 3.7: Simulations in East6
- 3.8: Interim Monitoring
- Chapter 4: Data Editor
- Volume 2: Continuous Endpoints
- Chapter 5: Introduction to Volume 2
- Chapter 6: Tutorial: Normal Endpoint
- Chapter 7: Normal Superiority One-Sample
- Chapter 8: Normal Noninferiority Paired-Sample
- Chapter 9: Normal Equivalence Paired-Sample
- Chapter 10: Normal Superiority Two-Sample
- Chapter 11: Nonparametric Superiority Two Sample
- Chapter 12: Normal Non-inferiority Two-Sample
- Chapter 13: Normal Equivalence Two-Sample
- Chapter 14: Normal: Many Means
- Chapter 15: Multiple Comparison Procedures for Continuous Data
- Chapter 16: Multiple Endpoints-Gatekeeping Procedures
- Chapter 17: Continuous Endpoint: Multi-arm Multi-stage (MaMs) Designs
- Chapter 18: Two-Stage Multi-arm Designs using p-value combination
- Chapter 19: Normal Superiority Regression
- Volume 3: Binomial and Categorical Endpoints
- Chapter 20: Introduction to Volume 3
- Chapter 21: Tutorial: Binomial Endpoint
- Chapter 22: Binomial Superiority One-Sample
- Chapter 23: Binomial Superiority Two-Sample
- 23.1: Difference of Two Binomial Proportions
- 23.1.1: Trial Design
- Single Look Design
- Group Sequential Design
- Lan-DeMets Spending Function: O'Brien-Fleming Version
- Lan-DeMets Spending Function: Pocock Version
- Wang and Tsiatis Power Boundaries
- The Power Chart and the ASN Chart
- Unequally spaced analysis time points
- Arbitrary amounts of error probability to be spent at each analysis
- Computing power for a given sample size
- Stopping Boundaries for Early Rejection of H0 or H1
- Boundaries with Early Stopping for Benefit or Futility
- Multiple designs for discrete outcomes
- Select individual looks
- Simulation Tool
- 23.1.2: Interim Monitoring
- 23.1.3: Pooled versus Unpooled Designs
- 23.1.1: Trial Design
- 23.2: Ratio of Proportions
- 23.3: Odds Ratio of Proportions
- 23.4: Common Odds Ratio of Stratified Tables
- 23.5: Fisher's Exact Test (Single Look)
- 23.6: Assurance (Probability of Success)
- 23.7: Predictive Power and Bayesian Predictive Power
- 23.1: Difference of Two Binomial Proportions
- Chapter 24: Binomial Non-Inferiority Two-Sample
- Chapter 25: Binomial Equivalence Two-Sample
- Chapter 26: Binomial Superiority n-Sample
- 26.1: Chi-Square for Specified Proportions in C Categories
- 26.2: Two-Group Chi-square for Proportions in C Categories
- 26.3: Nonparametric: Wilcoxon Rank Sum for Ordered Categorical Data
- 26.4: Trend in R Ordered Binomial Proportions
- 26.5: Chi-Square for R Unordered Binomial Proportions
- 26.6: Chi-Square for R Unordered Multinomial Proportions
- Chapter 27: Multiple Comparison Procedures for Discrete Data
- Chapter 28: Multiple Endpoints-Gatekeeping Procedures for Discrete Data
- Chapter 29: Two-Stage Multi-arm Designs using p-value combination
- Chapter 30: Binomial Superiority Regression
- Chapter 31: Agreement
- Chapter 32: Dose Escalation
- Volume 4: Exact Binomial Designs
- Volume 5: Poisson and Negative Binomial Endpoints
- Volume 6: Time to Event Endpoints
- Chapter 42: Introduction to Volume 6
- Chapter 43: Tutorial: Survival Endpoint
- 43.1: A Quick Feel of the Software
- 43.2: Group Sequential Design for a Survival Superiority Trial
- 43.2.1: Background Information on the study
- 43.2.2: Creating the design in East
- 43.2.3: Design Outputs
- 43.2.4: East icons explained
- 43.2.5: Saving created Designs in the library and hard disk
- 43.2.6: Displaying Detailed Output
- 43.2.7: Comparing Multiple Designs
- 43.2.8: Events vs. Time plot
- 43.2.9: Simulation
- 43.2.10: Interim Monitoring
- 43.3: User Defined R Function
- Chapter 44: Superiority Trials with Variable Follow-Up
- 44.1: The RALES Clinical Trial: Initial Design
- 44.2: Incorporating Drop-Outs
- 44.3: Incorporating Non-Constant Accrual Rates
- 44.4: Incorporating Piecewise Constant Hazards
- 44.5: Simulating a Trial with Proportional Hazards
- 44.6: Simulating a Trial with Non-Proportional Hazards
- 44.7: Simulating a Trial with Stratification variables
- Chapter 45: Superiority Trials with Fixed Follow-Up
- Chapter 46: Non-Inferiority Trials Given Accrual Duration and Accrual Rates
- Chapter 47: Non-Inferiority Trials with Fixed Follow-Up
- Chapter 48: Superiority Trials Given Accrual Duration and Study Duration
- Chapter 49: Non Inferiority Trials Given Accrual Duration and Study Duration
- Chapter 50: A Note on Specifying Dropout parameters in Survival Studies
- Chapter 51: Multiple Comparison Procedures for Survival Data
- Volume 7: Adaptive Designs
- Chapter 52: Introduction To Adaptive Features
- Chapter 53: The Motivation for Adaptive Sample Size Changes
- Chapter 54: The Cui, Hung and Wang Method
- Chapter 55: The Chen, DeMets and Lan Method
- Chapter 56: Muller and Schafer Method
- 56.1: Statistical Method
- 56.2: Implementation of Hypothesis Testing
- 56.2.1: Designing the Primary Trial
- 56.2.2: Monitoring the Primary Trial
- 56.2.3: Making Adaptive Changes to Primary Trial
- 56.2.4: Implementing Adaptive Changes through Secondary Trial
- 56.2.5: Reconstructing a Combined Trial from the Primary and Secondary Trials
- 56.2.6: Verifying Operating Characteristics by Simulation
- 56.3: Implementation of Parameter Estimation
- 56.4: Survival Endpoint: Pancreatic Cancer Trial
- Chapter 57: Conditional Power for Decision Making
- Volume 8: Special Topics
- Chapter 58: Introduction to Volume 8
- Chapter 59: Design and Monitoring of Maximum Information Studies
- Chapter 60: Design and Interim Monitoring with General Endpoints
- Chapter 61: Early Stopping for Futility
- 61.1: Example: Survival in patients with advanced melanoma
- 61.2: Single-Look Design with No Early Stopping
- 61.3: Group Sequential Design with Early Stopping for Efficacy
- 61.4: Informal Use of Conditional Power for Futility Stopping
- 61.5: Combined Efficacy and Futility Stopping Boundaries
- 61.6: Early Stopping for Futility Only
- Chapter 62: Flexible Stopping Boundaries in East
- Chapter 63: Confidence Interval Based Design
- 63.1: One Sample Test for a Single Mean for Continuous Data
- 63.2: One Sample Test for the Mean of Paired Differences for Continuous Data
- 63.3: Two Sample Test for the Difference of Means for Continuous Data
- 63.4: One Sample Test for a Single Binomial Proportion
- 63.5: Two Sample Test for the Difference of Binomial Proportions
- 63.6: Two Sample Test for the Ratio of Binomial Proportions
- 63.7: Two Sample Test for the Odds Ratio of Proportions
- 63.8: One Sample Test for McNemar's Test for Comparing Matched Pairs
- 63.9: Many Sample Test - One Way ANOVA
- 63.10: Many Sample Test - One Way Repeated Measures
- 63.11: Normal Test for Linear Regression - Single Slope
- 63.12: Normal Test for Linear Regression - Difference of Slopes
- Chapter 64: Simulation in East
- Chapter 65: Predictive Interval Plots
- Chapter 66: Enrollment/Events Prediction - At Design Stage (By Simulation)
- Chapter 67: Conditional Simulation
- Chapter 68: Enrollment/Events Prediction - Analysis
- Chapter 69: Interfacing with East PROCs
- Volume 9: Analysis
- Chapter 70: Introduction to Volume 9
- Chapter 71: Tutorial: Analysis
- Chapter 72: Analysis-Descriptive Statistics
- Chapter 73: Analysis-Analytics
- Chapter 74: Analysis-Plots
- Chapter 75: Analysis-Normal Superiority One-Sample
- Chapter 76: Analysis-Normal Noninferiority Paired-Sample
- Chapter 77: Analysis-Normal Equivalence Paired-Sample
- Chapter 78: Analysis-Normal Superiority Two-Sample
- Chapter 79: Analysis-Normal Noninferiority Two-Sample
- Chapter 80: Analysis-Normal Equivalence Two-Sample
- Chapter 81: Analysis-Nonparametric Two-Sample
- Chapter 82: Analysis-ANOVA
- Chapter 83: Analysis-Regression Procedures
- Chapter 84: Analysis-Multiple Comparison Procedures for Continuous Data
- 84.1: Available Procedures
- 84.2: Example: Dunnett's single step
- 84.3: Example: Dunnett's step-down and step-up procedures
- 84.4: p-value based Procedures
- 84.5: Single step MC procedures
- 84.6: Step down MC procedure
- 84.7: Data-driven step-up MC procedures
- 84.8: Fixed-sequence stepwise MC procedures
- 84.9: Example: Raw p-values as input
- Chapter 85: Analysis-Multiple Endpoints for Continuous Data
- Chapter 86: Analysis-Binomial Superiority One-Sample
- Chapter 87: Analysis-Binomial Superiority Two-Sample
- 87.1: Example: Difference of Proportions-Asymptotic
- 87.2: Example: Difference of Proportions-Exact
- 87.3: Example: Ratio of Proportions-Asymptotic
- 87.4: Example: Ratio of Proportions-Exact
- 87.5: Example: Odds Ratio of Proportions
- 87.6: Example: Common Odds Ratio of Proportions for stratifies 2X2 tables
- 87.7: Example: Fisher's Exact Test
- Chapter 88: Analysis-Binomial Noninferiority Two-Sample
- Chapter 89: Analysis-Binomial Equivalence Two-Samples
- Chapter 90: Analysis-Discrete: Many Proportions
- 90.1: Example: Chi-square Test of Specified Proportions
- 90.2: Example: Two group Chi-square test
- 90.3: Example: Wilcoxon Rank Sum Test for Ordered Categories Data
- 90.4: Example: Trend in R ordered proportions
- 90.5: Example: Chi-Square Test for R 2 Proportions
- 90.6: Example: Chi-square Test for Prop in RxC Tables
- Chapter 91: Analysis-Binary Regression Analysis
- Chapter 92: Analysis- Multiple Comparison Procedures for Binary Data
- Chapter 93: Analysis-Comparison of Multiple Comparison Procedures for Continuous Data- Analysis
- Chapter 94: Analysis-Multiple Endpoints for Binary Data
- Chapter 95: Analysis-Agreement
- Chapter 96: Analysis-Survival Data
- 96.1: Superiority
- 96.2: Example: Survival Superiority Two Samples:Logrank
- 96.3: Example :Survival Superiority Two Samples: Wilcoxon-Gehan
- 96.4: Example:Survial Superiority Two Samples: Harrington-Fleming
- 96.5: Example: Survival Noninferiority two Samples:Logrank
- 96.6: Example: Survival Noninferiority two Samples-Wilcoxon
- 96.7: Example: Survival Noninferiority two Samples:Harrington-Fleming
- 96.8: Example: Survival Multi-arm-Kaplan Meier Estimator
- Chapter 97: Analysis-Multiple Comparison Procedures for Survival Data
- Volume 10: Appendices
- Appendix A: Introduction to Volume 10
- Appendix B: Group Sequential Design in East 6
- Appendix C: Interim Monitoring in East 6
- C.1: Flexible Interim Monitoring
- C.2: Post-Hoc Power and Preservation of Error
- C.3: Conditional Power at Ideal Next Look Position (East 5.4)
- C.4: Conditional and predictive power (East 6)
- C.5: Repeated Confidence Intervals
- C.6: Inference Following Group Sequential Testing
- C.7: Monitoring Data from any General Distribution
- C.8: Information Based Monitoring
- Appendix D: Computing the Expected Number of Events
- Appendix E: Generating Survival Simulations in EastSurv
- Appendix F: Spending Functions Derived from Power Boundaries
- Appendix G: The Recursive Integration Algorithm
- Appendix H: Theory - Multiple Comparison Procedures
- H.1: Parametric Procedures
- H.2: P-value based procedures
- H.2.1: Hypotheses, test statistics and marginal p-values for continuous response
- H.2.2: Hypotheses, test statistics and marginal p-values for binary response
- H.2.3: Bonferroni Procedure
- H.2.4: Sidak Procedure
- H.2.5: Weighted Bonferroni Procedure
- H.2.6: Holm Step-Down Procedure
- H.2.7: Hochberg Step-Up Procedure
- H.2.8: Fixed Sequence Testing Procedure
- H.2.9: Hommel Step-Up Procedure
- H.2.10: Fallback Procedures
- H.3: Generate Means/Proportions through DR Curves
- Appendix I: Theory - Multiple Endpoint Procedures
- Appendix J: Theory-Multi-arm Multi-stage Group Sequential Design
- Appendix K: Theory - MultiArm Two Stage Designs Combining p-values
- Appendix L: Technical Details - Predicted Interval Plots
- Appendix M: Enrollment/Events Prediction - Theory
- Appendix N: Dose Escalation - Theory
- Appendix O: R Functions
- O.1: Introduction
- O.2: Initialization Function
- O.3: Data Generation Functions
- O.4: Generating Continuous Response
- O.4.1: Response for Single Mean Test
- O.4.2: Response for Mean of Paired Differences Test
- O.4.3: Response for Difference of Means Test
- O.4.4: Response for Mean of Paired Ratio Test
- O.4.5: Generating Response for Ratio of Means Test
- O.4.6: Generating Binary Response Values
- O.4.7: Generating Categorical Response Values
- O.4.8: Generating Survival Times
- O.5: Enhanced Simulations
- O.6: Suggested Formats
- O.7: Basic Simulation
- O.8: Output from R function
- O.9: Suggested Formats
- O.10: Treatment Selection Function
- O.11: Functions for Adaptive Simulations
- O.12: Use of Initialization Function
- O.13: Additional Arguments
- Appendix P: East 5.x to East 6.4 Import Utility
- Appendix Q: Technical Reference and Formulas: Single Look Designs
- Q.1: Introduction
- Q.2: Common Notation
- Q.3: Sample Size : Continuous
- Q.3.1: Single Arm Design : Single Mean : Superiority: Test Statistic Distribution: Normal
- Q.3.2: Single Arm Design : Single Mean : Superiority: Test Statistic Distribution: t
- Q.3.3: Paired Design: Superiority: Test Statistic Distribution: Normal:Mean of paired differences
- Q.3.4: Paired Design: Superiority: Test Statistic Distribution: t
- Q.3.5: Paired Design : Non-inferiority: Test Statistic Distribution: Normal
- Q.3.6: Paired Design : Non-inferiority: Test Statistic Distribution: t
- Q.3.7: Paired Design : Equivalence: Test Statistic Distribution: t
- Q.3.8: Paired Design: Superiority: Test Statistic Distribution: Normal: Mean of Paired Ratios
- Q.3.9: Paired Design: Superiority: Test Statistic Distribution: t
- Q.3.10: Paired Design : Non-inferiority: Test Statistic Distribution: Normal
- Q.3.11: Paired Design : Non-inferiority: Test Statistic Distribution: t
- Q.3.12: Paired Design : Equivalence: Test Statistic Distribution: t
- Q.4: Sample Size : Continuous:Two Samples
- Q.4.1: Two Independent Samples:Superiority:Test Statistic Dist: Normal
- Q.4.2: Two Independent Samples: Superiority: Test Statistic Distribution: t: Variance : Equal
- Q.4.3: Two Independent Samples: Superiority: Test Statistic Distribution: t Variance : Unequal
- Q.4.4: Two Independent Samples: Non-inferiority : Test Statistic Distribution: Normal
- Q.4.5: Two Independent Samples: Non-inferiority : Test Statistic Distribution: t Variance : Equal
- Q.4.6: Two Independent Samples: Non-inferiority : Test Statistic Distribution: t: Variance : Unequal
- Q.4.7: Two Independent Samples: Equivalence:Test Statistic Distribution:t
- Q.4.8: Two Independent Samples: Superiority: Test Statistic Distribution: Normal: Variance: Equal
- Q.4.9: Two Independent Samples: Superiority: Test Statistic Distribution: t:Variance : Equal
- Q.4.10: Two Independent Samples: Non-inferiority : Test Statistic Distribution: Normal
- Q.4.11: Two Independent Samples: Non-inferiority : Test Statistic Distribution: t
- Q.4.12: Two Independent Samples: Equivalence : Test Statistic Distribution: t
- Q.4.13: Two Independent Samples: Wilcoxon Mann Whitney Test
- Q.5: Sample Size : Continuous : Crossover Designs : Two Samples
- Q.5.1: Crossover Designs :Superiority : Test Statistic Distribution: t
- Q.5.2: Crossover Designs :Noninferiority : Test Statistic Distribution:t
- Q.5.3: Crossover Designs :Equivalence : Test Statistic Distribution: t
- Q.5.4: Crossover Designs: Superiority: Test Statistic Distribution: t
- Q.5.5: Crossover Designs :Noninferiority : Test Statistic Distribution: t
- Q.5.6: Crossover Designs :Equivalence : Test Statistic Distribution: t
- Q.6: Sample Size : Continuous : Many Samples
- Q.6.1: One Way ANOVA : Superiority: Test Statistic Distribution: F
- Q.6.2: One Way ANOVA : Single One Way Contrast: t
- Q.6.3: One Way Repeated Measures: ANOVA: Superiority: Constant Correlation
- Q.6.4: One Way Repeated Measures Contrast
- Q.6.5: Two Way ANOVA
- Q.6.6: Linear regression single slope
- Q.6.7: Linear Regression : Difference of slopes
- Q.6.8: Repeated measures: Difference of slopes
- Q.7: Sample Size : Discrete
- Q.7.1: Single Arm Design : Single Proportion : Superiority: Test Statistic Distribution: Normal:Variance: Under Null hypothesis
- Q.7.2: Single Arm Design : Single Proportion : Superiority: Test Statistic Distribution: Normal:Variance: Empirical
- Q.7.3: Paired Design: McNemar's Test: Superiority: Test Statistic Distribution: Normal
- Q.8: Sample Size :Discrete : Two Samples
- Q.8.1: Two Independent Samples : Difference of Proportions: Superiority: Test Statistic Distribution: Normal:Variance:Unpooled estimate
- Q.8.2: Two Independent Samples : Difference of Proportions: Superiority: Test Statistic Distribution: Normal: Variance : Pooled estimate
- Q.8.3: Two Independent Samples : Difference of Proportions: Noninferiority: Test Statistic Distribution: Normal
- Q.8.4: Two Independent Samples : Difference of Proportions: Equivalence: Test Statistic Distribution: Z
- Q.8.5: Two Independent Samples : Ratio of Proportions: Superiority: Test Statistic Distribution: Normal :Variance: Unpooled
- Q.8.6: Two Independent Samples : Ratio of Proportions: Superiority: Test Statistic Distribution: Normal: Variance: Pooled
- Q.8.7: Two Independent Samples : Ratio of Proportions: Noninferiority: Farrington and Manning: Test Statistic Distribution: Normal
- Q.8.8: Two Independent Samples : Ratio of Proportions: Noninferiority: Wald's Test: Test Statistic Distribution: Normal
- Q.8.9: Two Independent Samples : Odds Ratio of Proportions: Superiority: Test Statistic Distribution: Normal
- Q.8.10: Two Independent Samples : Odds Ratio of Proportions: Noninferiority: Test Statistic Distribution: Normal
- Q.8.11: Two Independent Samples : Common Odds Ratio for Stratified 2 2 tables: Superiority: Test Statistic Distribution: Normal
- Q.9: Sample Size :Discrete : Many Samples
- Q.9.1: Many Samples: Single Arm: Chi-square for specified proportions in C categories
- Q.9.2: Many Samples: Parallel Design: Two group Chi-square for proportions in C categories
- Q.9.3: Many Samples: Parallel Design: Wilcoxon Rank Sum for ordered categorical data
- Q.9.4: Many Samples: Multi-arm: Trend in R ordered proportions
- Q.9.5: Many Samples: Multi-arm: Chi-square for Rx2 proportions
- Q.9.6: Many Samples: Multi-arm: Chi-square for proportions in RxC tables
- Q.10: Sample Size :Discrete : Regression
- Q.11: Sample Size : Agreement
- Q.12: Sample Size : Count Data
- Q.13: Sample Size :Time to Event Data
- Appendix R: Technical Reference and Formulas: Analysis
- R.1: Basic Statistics- Descriptive Statistics
- R.2: Basic Statistics-Analytics
- R.3: Continuous
- R.4: Discrete
- R.5: Two Independent Binomials
- R.5.1: Exact Unconditional Test of Superiority : Difference of Proportions
- R.5.2: Exact Test of Noninferiority:Difference of Proportions
- R.5.3: Exact Test of Equivalence: Difference of Proportions
- R.5.4: Unconditional Exact Confidence Intervals for the Difference of Proportions
- R.5.5: Unconditional Exact Confidence Intervals for the Ratio of Proportions
- R.5.6: Exact Test of Noninferiority:Ratio of Proportions
- R.5.7: Unconditional Exact Confidence Interval for the Ratio of Proportions
- R.5.8: Searching for Nuisance Parameters in a Restricted Range: Berger-Boos Correction
- R.5.9: Noninferiority:Odds Ratio of Proportions
- R.5.10: Common Odds Ratio for Stratified 2x2 Tables
- R.5.11: Fisher's Exact Test
- R.6: Many Proportions
- R.7: Agreement
- R.8: Survival : Two Samples
- Appendix S: Theory - Design - Binomial One-Sample Exact Test
- Appendix T: Theory - Design - Binomial Paired-Sample Exact Test
- Appendix U: Theory - Design - Simon's Two-Stage Design
- Appendix V: Theory-Design - Binomial Two-Sample Exact Tests
- V.1: Fisher's Exact Test
- V.2: Power of Unconditional Test of Superiority
- V.3: Power of the Unconditional Test of Non-Inferiority
- V.4: Power of the Unconditional Test of Equivalence
- V.5: Sample Size Computations
- Appendix W: Classification Table
- Appendix X: Glossary
- Appendix Y: On validating the East Software
- Appendix Z: List of East Beta Testers
- References
- Index