Essentials of a Successful Biostatistical Collaboration

Essentials of a Successful Biostatistical Collaboration by Arul Earnest is a unique approach to a biostatistics text in that the focus is not purely on study design and statistical analyses. While these topics are certainly discussed, equal attention is given to topics such as planning, project management, and effective communication that are important for any biostatistician who is collaborating with a research team.

 

The book begins with an overview of observational study designs as well as randomized control trials. Then the discussion turns to data management, power and sample-size calculations, and a variety of statistical analyses. Earnest provides an overview of statistical methods ranging from basics such as t tests and correlation to more advanced topics such as Cox regression and ARIMA models, and each topic is accompanied by the corresponding Stata commands and output. The following chapters give advice on both verbal and written communication, project management, and how to manage collaborations.

 

This book is a practical resource that will appeal to biostatisticians, epidemiologists, and other members of clinical research teams as well as students who plan to work in this field.

Preface
Acknowledgements
Author

 

1. OBSERVATIONAL STUDY DESIGNS

Introduction

Comparative Features between Cohort, Case–Control and Cross-Sectional Studies

Cross-Sectional Study Design

Case–Control Study Design

Cohort Study Design

Ecological Study Design

Selecting the Appropriate Study Design

Key Questions to Ask a Clinician

Common Mistakes

Online Tools and Resources

A Collaborative Case Study

Study Summary

Alternative Study Designs

Key Learning Points

References

 

2. RANDOMISED CONTROLLED TRIALS

Introduction

Phases and Types of Trials

Types and Features of Randomisation

Controls and Blinding

Other Types of RCTs

Cluster RCT

Crossover Trials

Stepped Wedge Cluster RCT

Equivalence Trials

Data and Safety Monitoring Board

Choosing Outcome Measures for a Trial

Key Questions to Ask a Clinician

Tools and Resources

A Collaborative Case Study

Study Summary

Alternate Method of Randomisation

Significance of Trial

Rigorous and Appropriate Analysis

Key Learning Points

References

 

3. FORM DESIGN AND DATABASE MANAGEMENT

Introduction
Principles of Questionnaire Design

Open-Ended versus Closed-Ended Questions
Multiple-Response Questions
Double-Barrelled Questions
Wording of Questions
Ordinal Scales
Validation
Translation

Types of Variables and Scales of Measurement
Finding a Suitable Database Software for Your Study
Efficient Ways to Create and Manage an Excel Database

Multiple-Response Questions
Repeated Measurements
Missing Data
Data Validation in Excel
Limitations to Excel

Key Questions to Ask a Clinician
Common Mistakes to Avoid

Questionnaire Design
Database Design

Tools and Resources
A Collaborative Case Study

Key Learning Points
References

 

4. SAMPLE SIZE AND POWER CALCULATIONS

Introduction
Linking Hypothesis Testing and Sample Size
Ingredients in a Sample Size Calculation

Objective of the Study
Type 1 Error (Level of Significance)
Type 2 Error (1 – Power)
Variability
The Effect Size
Two-Sided versus One-Sided Tests
Other Considerations

Commonly Performed Sample Size Calculations

Comparing Proportions between Two Independent Groups
Comparing Means between Two Independent Groups
Estimating Hazard Ratios in a Survival (Time to Event) Analysis
Estimating Coefficients in a Linear Regression Model
Estimating Odds Ratios in a Logistic Regression Model
Estimating a Kappa Coefficient in an Agreement Study
Repeated Measures Analysis
Cluster Randomised Trials

Key Questions to Ask a Clinician
Common Mistakes
Tools and Resources
A Collaborative Case Study

Key Learning Points
References

 

 5. STATISTICAL ANALYSIS PLAN

Introduction
Choosing the Appropriate Statistical Method
Common Statistical Hypotheses and Tests

Univariate Analysis

Estimate Mean
Estimate Proportion

Bivariate Analysis

Compare Means in Two Groups
Assumptions of Independent Student’s t-Test
Non-Parametric Equivalent: Mann–Whitney U Test
Compare Means in More Than Two Groups
Assumptions of the ANOVA Test
Non-Parametric Equivalent: Kruskal–Wallis Test
Compare Means within the Same Group
Calculate Correlation between Two Continuous Variables
Compare Proportions
Compare Survival
Measure Agreement (Continuous Variables)
Measure Agreement (Categorical Variables)
Relative Risk Measures

Multi-Variate Analysis

Continuous Outcome Measure–Linear Regression Model
Assumptions of the Linear Regression Model
Binary Outcome Measure–Binary Logistic Regression Model
Predicted Probability
Ordinal Outcome Measure–Ordinal Logistic Regression
Categorical Outcome Measure–Multinomial Logistic Regression
Count Data–Poisson Regression Model
Survival Data–Cox Regression Model
Generalised Estimating Equations
Clinical Examples
ARIMA Models
Clinical Example

Issues to Note

Crossover Trials

Cluster RCT

Intention-to-Treat versus Per-Protocol Analysis

Missing Data

Multiplicity

Key Questions to Ask a Clinician

A Collaborative Case Study

Key Learning Points
References

 

6. EFFECTIVE COMMUNICATION SKILLS

Introduction

The Initial Meeting

Difficulty in Understanding Medical Jargon

Challenges in Explaining Statistical Concepts to Clinicians

Using the Venn Diagram

Using the Gaussian Curve

Simplifying Language

Employing Drawings

Effective Presentation Skills

Tips and Tricks within Microsoft PowerPoint for a Statistical Presentation

Actual Presentation

Preparing a Poster

Checklist for Preparing and Presenting an Effective Research Poster

Content

Layout and Format

Narrative Description

Some Tips on Creating a Poster in Microsoft PowerPoint

Tools and Resources

A Collaborative Case Study

Key Learning Points

References

 

7. EFFECTIVE WRITING SKILLS

Introduction

Writing a Statistical Analysis Plan for a Grant Application

Specific Aims and Hypotheses

Background and Clinical Significance

Preliminary Studies/Progress Report

Methods/Approach

CONSORT Statement

STROBE Statement

PRISMA Statement

STARD Statement

Writing for a Publication – First-Author Publication

Selecting the Journal

Instructions for Authors

Tips for Formatting

Preparing a Manuscript

Abstract

Tips for the Abstract Section

Introduction

Tips for the Introduction Section

Methods

Results

Tips for the Results Section

Discussion and Conclusion

Tips for the ‘Discussion and Conclusion’ Section

Creating a Draft

Writing for a Publication – Collaborative Publication

Additional Tips When Writing for a Collaborative Publication

Resources

Key Learning Points

References

 

8. PROJECT MANAGEMENT: BEST PRACTICES

Introduction

Creation of a Project File

Database Security and Confidentiality

Database Confidentiality

Database Security

Standard Operating Procedures

Ensuring Consistency and Reproducibility in the Results

Managing Multiple Projects

Obtaining Mentorship

Poor Project Management Skills (The ‘Not’s to Avoid)

A Collaborative Case Study

Key Learning Points

References

 

9. MANAGING COLLABORATIONS

Introduction

Getting the Most Out of a Collaboration

Providing Collaboration in a Large Complex Institution – Hub-and-Spoke Model

Providing Consultations

Seven Faces of Collaborators

The Auto-Pilot

The Pseudo-Statistician

The ‘Harry Houdini’

The p-Value Hunter

The Sceptic

The Passive Collaborator

The Faceless Collaborator

Useful Strategies to Adopt in Successfully Managing a Collaboration

Responding to Unreasonable Work Requests

Reasoning with a Collaborator Who Engages in Data Dredging

Coping with an Unreasonable Request on Turnaround Time

Negotiating Authorship

International Collaborators

General Statistical Conferences

Biostatistics Conferences

Key Learning Points

References

 

10. HOW NOT TO DESIGN, ANALYSE AND PRESENT YOUR STUDY

Introduction

Choosing the Inappropriate Study Design

Selecting Too Few Subjects in the Study

Incorrect Use of Randomisation

Undertaking Incorrect Statistical Tests

Not Checking for the Assumptions Behind the Test

Data Dredging

Presenting Tables and Figures Inappropriately

Reporting and Interpreting Data Inappropriately

Conclusion

Key Learning Points

References

 

11. VIEWS FROM THE GROUND: A SURVEY AMONG BIOSTATISTICIANS AND A CHAT WITH CLINICIANS

Introduction

Survey Methodology and Profile of Respondents

Problems Ever Faced in Collaborating with Clinicians

Training on Collaboration/Consultation Skills

Frequency of Performing Selected Tasks as a Biostatistician

Issues to Address in Order to Enhance Greater Collaborations

Skills Most Important to Gain to Improve on Collaborations with Clinicians

Formal Postgraduate Degrees

Short Courses

Online Course

Journals (Development and Application of Statistics in Medicine)

Views from Clinicians Who Have Collaborated with Biostatisticians

Interview with Dr. Leong Khai Pang, MBBS, FRCPE, FAMS

Interview with Professor Nick Paton, MB BChir (Cambridge), MRCP (Internal Medicine) (London), MD (Cambridge), FRCP (Edinburgh), DTM & H (London)

Interview with Professor John Augustus Rush, MD, AB

Interview with Professor John McNeil, AM, MBBS (Adelaide), MSc (London), PhD (Melbourne), FRACP, FAFPHM

Conclusion

Appendix: Sample Survey Questionnaire

Key Learning Points

References

Author: Arul Earnest
ISBN-13: 978-1-4822-2698-0
©Copyright: 2017 CRC Press

Essentials of a Successful Biostatistical Collaboration by Arul Earnest is a unique approach to a biostatistics text in that the focus is not purely on study design and statistical analyses. While these topics are certainly discussed, equal attention is given to topics such as planning, project management, and effective communication that are important for any biostatistician who is collaborating with a research team.