Practical Biostatistics
A Friendly Step-by-Step Approach for Evidence-based Medicine
- 1st Edition - July 26, 2012
- Authors: Mendel Suchmacher, Mauro Geller
- Language: English
Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of… Read more
Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of scientific methods and outcomes to drive further experimentation and diagnosis. The profusion of evidence-based medicine in medical practice and clinical research has produced a need for life scientists and clinical researchers to assimilate biostatistics into their work to meet efficacy and practical standards. Practical Biostatistics provides researchers, medical professionals, and students with a friendly, practical guide to biostatistics. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or a hands-on guide to effectively incorporate biostatistics in clinical trials.
- Customized presentation for biological investigators with examples taken from current clinical trials in multiple disciplines
- Clear and concise definitions and examples provide a pragmatic guide to bring clarity to the applications of statistics in improving human health
- Addresses the challenge of assimilation of mathematical concepts to better interpret literature, to build stronger studies, to present research effectively, and to improve communication with supporting biostatisticians
Investigators and clinicians involved in genetics, genomics, immunology, virology, microbiology, cell biology, pharmacology, and biomedical research; post-doctoral fellows and graduate researchers; physicians who need to make evidence-based clinical decisions; physicians and medical students who consult medical literature which demands knowledge on biostatistics; instructors and trainees in national and international technical clinician and degree programs
Foreword
Preface
Acknowledgments
Part I Introduction
Chapter 1. Study Type Determination
1.1 Epidemiological Studies
1.2 Analytical Studies
1.3 Summary of Study Types
Suggested Reading
Part II. Observational Studies
Chapter 2. Determination of Association Strength between an Exposure Factor and an Event in Observational Studies
2.1 Case–Control Studies
2.2 Cohort Studies
Chapter 3. Increasing Accuracy in Observational Studies
3.1 Stratified Analysis
3.2 Multivariable Analysis
Suggested Reading
Part III. Step-by-Step Biostatistics of a Clinical Trial
Chapter 4. Step 1: Investigator’s Hypothesis and Expression of its Corresponding Outcome
Chapter 5. Step 2: Estimation and Assessment of a Published Trial
5.1 Factors Influencing n Determination
5.2 n Calculation
5.3 Assessing n of a Published Trial
Chapter 6. Step 3: Organization of Variables and Endpoints
6.1 Qualitative Variables
6.2 Quantitative Variables
Chapter 7. Step 4: Measures for Results Expression of a Clinical Trial
7.1 Central Tendency Measures
7.2 Dispersal Measures
7.3 Position Measures: Quantiles
Appendix 7.1 How to Calculate Mean Using Microsoft Excel (Section 7.1.1)
Appendix 7.2 How to “Trim” The Mean of Outliers (Section 7.1.1)
Appendix 7.3 How to Determine Median Using Microsoft Excel (Section 7.1.2)
Appendix 7.4 How to Determine Mode Using Microsoft Excel (Section 7.1.3)
Appendix 7.5 How to Calculate Standard Deviation Using Microsoft Excel (Section 7.2.2)
Appendix 7.6 How to Find the Exact BMI that Corresponds to the 90th Percentile using Microsoft Excel (Section 7.3)
Appendix 7.7 How to Put all BMIs in a “Rank and Percentile” Perspective using Microsoft Excel (Section 7.3)
Chapter 8. Step 5: Determination of Normality or Non-Normality of Data Distribution
Appendix 8.1 How to Verify Normality of a Graph Curve Using Microsoft Excel
Chapter 9. Step 6: Hypothesis Testing
9.1 Parametric Tests for Independent and Dependent Samples
9.2 Nonparametric Tests
Chapter 10. Step 7: Correlating Sample Data with the General Population – 95% Confidence Interval
10.1 Point Estimation
10.2 Interval Estimation (95% Confidence Interval)
Appendix 10.1 How to Determine Confidence Intervals Using Microsoft Excel (Sample A)
Suggested Reading
Part IV. Additional Concepts in Biostatistics
Chapter 11. Individual and Collective Benefit and Risk Indexes Inferable from Intervention Studies
11.1 Treatment Effect Indexes
11.2 Clinical Decision Analysis Indexes
Chapter 12. Statistical Assessment of Diagnostic Tests for the Clinic
12.1 Detection Capacity Indexes
12.2 Diagnostic Significance Indexes
Chapter 13. Systematic Reviews and Meta-Analyses
13.1 Definitions
13.2 Systematic Review
13.3 Meta-Analysis
13.4 Options if Meta-Analysis Performance is not Advisable
13.5 Systematic Review/Meta-Analysis Limitations
13.6 Systematic Review/Meta-Analysis Stages Summary
13.7 Suggested Resources and Literary Sources
Chapter 14. Correlation and Regression
14.1 Correlation
14.2 Regression
14.3 Multiple Linear Regression
Appendix 14.1 How to Build a Scatterplot and to Add a Trend Line Using Microsoft Excel
Appendix 14.2 How to Calculate Pearson’s Correlation Coefficient Using Microsoft Excel
Appendix 14.3 How to Predict a Dependent Variable Using Microsoft Excel
Chapter 15. Per Protocol Analysis and Intention to Treat Analysis
Suggested Reading
APPENDIX. Microsoft Excel 2010 Basics
A.1 Structure and Main Features of a Microsoft Excel 2010 Worksheet
A.2 Location of Statistical Resources
A.3 Building a Plain Table
A.4 Building a Basic Chart
A.5 Building a Chart Out of a Table
A.6 Pivot Table
Suggested Reading
Glossary
Index
- Edition: 1
- Published: July 26, 2012
- Language: English
MS
Mendel Suchmacher
Mendel Suchmacher, MD, MSc, graduated in Pharmaceutical Medicine at Federal University of the State of São Paulo, is Board Certified in Internal Medicine and Hematology-Hemotherapy and member of the American College of Physicians. He holds teaching and research positions at prestigious Brazilian institutions: Professor of Clinical Immunology at Carlos Chagas Institute of Medical Graduation; Professor & Chairman of Microbiology and Immunology, and Research Fellow at Teresopolis University Medical School - UNIFESO; Professor & Coordinator of the Genodermatoses Sector of the Clinical Genetics Service at Federal University of Rio de Janeiro. Additionally, he is member of the clinical staff of Hospital Israelita Albert Einstein.
Affiliations and expertise
Carlos Chagas Institute of Medical Graduation; Teresopolis University Medical School - UNIFESO; Genodermatoses Sector of the Clinical Genetics Service, Federal University of Rio de Janeiro, BrazilMG
Mauro Geller
Mauro Geller, MD, PhD, holds an MD degree from Teresopolis University Medical School, a PhD in Clinical Medicine from Federal University of Rio de Janeiro, and a Post-doc in Immunogenetics from Harvard University. He has extensive experience in the field of clinical immunology, especially in the areas of clinical medicine, tumoral immunology, genetics and immunodiagnostics. Dr. Geller is founding member and current medical director of the Brazilian National Neurofibromatosis Center; fellow of the American College of Physicians and of the Royal Society of Medicine; member of the European Society of Gene Therapy; and member of the Brazilian Societies of Immunology, Microbiology and Genetics. He is Board Certified in Internal Medicine, Immunology, Allergy and Public Health. Dr. Geller also has extensive experience with research in the areas of immunology, microbiology and genetics, as well as with clinical research, and has published 137 papers, 8 book chapters, and 4 books. He also serves as ad hoc advisor to the Brazilian National Institute of Health (ANVISA) and is member of the clinical staff of Hospital Israelita Albert Einstein.
Affiliations and expertise
MD degree, Teresopolis University Medical School
PhD, Clinical Medicine, Federal University of Rio de Janeiro
Post-doc, Immunogenetics, Harvard UniversityRead Practical Biostatistics on ScienceDirect