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Confidence Intervals for Discrete Data in Clinical Research
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Main description:

Confidence Intervals for Discrete Data in Clinical Research is designed as a toolbox for biomedical researchers. Analysis of discrete data is one of the most used yet vexing areas in clinical research. The array of methodologies available in the literature to address the inferential questions for binomial and multinomial data can be a double-edged sword. On the one hand, these methods open a rich avenue of exploration of data; on the other, the wide-ranging and competing methodologies potentially lead to conflicting inferences, adding to researchers' confusion and frustration and also leading to reporting bias. This book addresses the problems that many practitioners experience in choosing and implementing fit for purpose data analysis methods to answer critical inferential questions for binomial and count data.

The book is an outgrowth of the authors' collective experience in biomedical research and provides an excellent overview of inferential questions of interest for binomial proportions and rates based on count data, and reviews various solutions to these problems available in the literature. Each chapter discusses the strengths and weaknesses of the methods and suggests practical recommendations. The book's primary focus is on applications in clinical research, and the goal is to provide direct benefit to the users involved in the biomedical field.


Contents:

1. Evidence and Inference

Terminology and Paradigm of Inference

Classical Inference

Hypothesis Tests and P-Values

Confidence Intervals

Criticisms of Classical Methods

The Bayesian Approach

Large Sample Inference

Robust Methods Are Preferred in Clinical Trials

Summary

2. 2 x 2 Tables

Measures of Treatment Effect

Exact Tests and Confidence Intervals

Fisher's Exact Test

Exact Confidence Interval for Odds Ratio

Oddities of Fisher's Exact Test and Confidence Interval

Unconditional Tests As Alternatives to Fisher's Exact Test

Appendix: P(X = x | S = s) in Table

Summary

3. Introduction to Clinical Trials

Summary

4. Design of Clinical Trials

Different Phases of Trials

Blinding

Baseline Variables

Controls

Regression to the Mean

Appropriate Control

Choice of Primary Endpoint

Reducing Variability

Replication and Averaging

Differencing

Stratification

Regression

Different Types of Trials

Superiority Versus Noninferiority

Parallel Arm Trials

Crossover Trials

Cluster-Randomized Trials

Multi-Arm Trials

Appendix: The Geometry of Stratification

Summary

5. Randomization/Allocation

Sanctity and Placement of Randomization

Simple Randomization

Permuted Block Randomization

Biased Coin Randomization

Stratified Randomization

Minimization and Covariate-Adaptive Randomization

Response-Adaptive Randomization

Adaptive Randomization And Temporal Trends

Summary

6. Randomization-Based Inference

Introduction

Paired Data

An Example

Control of Conditional Type Error Rate

Asymptotic Equivalence to a T-test

The Null Hypothesis and Generalizing

Does A Re-randomization Test Assume Independence?

Unpaired Data: Traditional Randomization

Introduction

Control of Conditional Type Error Rate

The Null Hypothesis and Generalizing

Does a Re-randomization Test Require Independence?

Asymptotic Equivalence to a t-Test

Protection Against Temporal Trends

Fisher's Exact Test As a Re-Randomization Test

Unpaired Data: Covariate-Adaptive Randomization

Introduction

Control of Conditional Type Error Rate

Protection Against Temporal Trends

A More Rigorous Null Hypothesis

Unpaired Data: Response-Adaptive Randomization

Introduction

Re-randomization Tests & Strength of Randomized Evidence

Confidence Intervals

A Philosophical Criticism of Re-randomization Tests

Appendix: The Permutation Variance of - YC - YT

Summary

7. Survival Analysis

Introduction to Survival Methods

Comparing Survival Across Arms

Comparing Survival At A Specific Time

The Logrank Test

The Hazard Rate and Cox Model

Competing Risk Analysis

Parametric Approaches

Conditional Binomial Procedure

Appendix: Partial Likelihood

Summary

8. Sample Size/Power

Introduction

The EZ Principle Illustrated through the -Sample t-Test

Important Takeaways from the EZ Principle

EZ Principle Applied More Generally

-Sample t-test

Test of Proportions

Logrank Test

Cluster-Randomized Trials

In a Nutshell

Nonzero Nulls

Practical Aspects of Sample Size Calculations

Test of Means

Test of Proportions

Specification of Treatment Effect

Exact Power

t-Tests

Exact Power for Fisher's Exact Test

Adjusting for Noncompliance and Other Factors

Appendix: Other Sample Size Formulas for Two Proportions

Summary

9. Monitoring

Introduction

Efficacy Monitoring

A Brief History of Efficacy Boundaries

Z-scores, B-Values, and Information

Revisiting O'Brien-Fleming

Alpha Spending Functions

The Effect of Monitoring on Power

Small Sample Sizes

Futility Monitoring

What is Futility?

Conditional Power

Beta Spending Functions

Practical Aspects of Monitoring

Inference after A Monitored Trial

Statistical Contrast between Unmonitored and Monitored Trials

Defining A P-Value after a Monitored Trial

Defining A Confidence Interval after A Monitored Trial

Correcting Bias after A Monitored Trial

Bayesian Monitoring

Summary

10. M&Ms: Multiplicity & Missing Data

Introduction

Multiple Comparisons

The Debate

Control of Familywise Error Rate (FWER)

Showing Strong Control by Enumeration

Intuition Behind Multiple Comparison Procedures

Independent Comparisons

Closure Principle

The Dunnett Procedure And A Conditioning Technique

Missing Data

Definitions And An Example

Methods for Data That Are MAR

Sensitivity Analyses

Summary

11. Adaptive Methods

Introduction

Adaptive Sample Size Based on Nuisance Parameters

Continuous Outcomes

Binary Outcomes

Adaptive Sample Size Based on Treatment Effect

Introduction and Notation

Non-adaptive Two-Stage Setting

Adaptation Principle

Bauer-Kohne ()

Proschan and Hunsberger, ()

Criticisms of Adaptive Methods Based on The Treatment Effect

Unplanned Changes before Breaking the Blind

Summary

Index


PRODUCT DETAILS

ISBN-13: 9781138048980
Publisher: Taylor & Francis (CRC Press)
Publication date: November, 2021
Pages: 300
Weight: 652g
Availability: Not available (reason unspecified)
Subcategories: Epidemiology

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