Practical Biostatistics
A Step-by-Step Approach for Evidence-Based Medicine
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Practical Biostatistics: A Step-by-Step Approach for Evidence-Based Medicine, Second Edition presents a complete resource of biostatistical knowledge meant for health sciences students, researchers and health care professionals. The book's content covers the investigator’s hypothesis, collective health, observational studies, the biostatistics of intervention studies, clinical trials and additional concepts. Chapters are written in a didactic way, making them easier to comprehend by readers with little or no background on statistics. Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision-making using statistical analyses of scientific methods and outcomes to drive further experimentation and diagnosis. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or hands-on guide on how to effectively incorporate biostatistics in clinical trials and research projects.
Key Features
- Explains biostatistics in a didactic way for students, researchers and professionals of health sciences with little or no background on mathematics
- Presents a new section dedicated to epidemiology and public health, broadening content from the previous edition
- Written by medical doctors with vast experience on biostatistics and teaching who develop the content based on real cases for better applicability by readers
Readership
Biostaticians; graduate students and researchers from medical and biomedical fields
Table of Contents
- Cover image
- Title page
- Table of Contents
- Copyright
- About the authors
- Part 1: The investigator's hypothesis
- Part 1. The investigator's hypothesis
- Chapter 1. Investigator’s hypothesis and expression of its corresponding outcome
- Abstract
- Part 2: Collective health
- Part 2. Collective health
- Chapter 2. Disease frequency measures
- Abstract
- 2.1 Preamble
- 2.2 Simple count
- 2.3 Prevalence
- 2.4 Incidence
- 2.5 Relationship between prevalence and incidence
- Chapter 3. Health indicators
- Abstract
- 3.1 Preamble
- 3.2 Survival
- 3.3 Mortality
- 3.4 Life indicators
- 3.5 Morbidity indicators
- Chapter 4. Epidemiological studies
- Abstract
- 4.1 Ecological studies
- 4.2 Cross-sectional studies
- 4.3 Longitudinal studies
- Chapter 5. Pharmacoeconomics
- Abstract
- 5.1 Costs and benefits
- 5.2 Cost-oriented timing
- 5.3 Costs minimization analysis
- 5.4 Cost–efficacy analysis
- 5.5 Utility
- 5.6 Financial resources
- 5.7 Health-related life quality—using questionnaires
- 5.8 Decision analysis
- Bibliography
- Suggested reading
- Part 3: Observational studies
- Part 3. Observational studies
- Chapter 6. Basic concepts in observational studies
- Abstract
- 6.1 Case-control studies
- 6.2 Cohort studies
- Chapter 7. Determination of association strength between an exposure factor and an event in observational studies
- Abstract
- 7.1 Case-control studies
- 7.2 Cohort studies
- Chapter 8. Increasing accuracy in observational studies
- Abstract
- 8.1 Stratified analysis
- 8.2 Multivariable analysis
- Bibliography
- Suggested reading
- Part 4: Biostatistics of intervention studies–The clinical trials
- Part 4. Biostatistics of intervention studies–The clinical trials
- Chapter 9. The intervention studies
- Abstract
- 9.1 Reference standard
- 9.2 Relation between samples and of a sample with itself
- 9.3 Awareness of tested drug, vaccine, or exam
- 9.4 Study subject allocation method
- 9.5 Follow-up method
- 9.6 Subgroup analysis
- Chapter 10. n Estimation and n assessment of a published trial
- Abstract
- 10.1 Factors influencing n determination
- 10.2 n Estimate
- 10.3 Assessing n of a published trial
- Chapter 11. Organization of variables and endpoints
- Abstract
- 11.1 Qualitative variables
- 11.2 Quantitative variables
- Chapter 12. Measures for results expression of a clinical trial
- Abstract
- 12.1 Central tendency measures
- 12.2 Dispersal measures
- 12.3 Position measures: quantiles
- Chapter 13. Determination of normality or nonnormality of data distribution
- Abstract
- Chapter 14. Hypothesis testing
- Abstract
- 14.1 Parametric tests for independent and dependent samples
- 14.2 Nonparametric tests
- Chapter 15. Correlating sample data with the general population—95% confidence interval
- Abstract
- 15.1 Point estimation
- 15.2 Interval estimation (95% confidence interval)
- Bibliography
- Suggested reading
- Part 5: Additional concepts in biostatistics
- Part 5. Additional concepts in biostatistics
- Chapter 16. Individual and collective benefit and risk indexes inferable from intervention studies
- Abstract
- 16.1 Treatment effect indexes
- 16.2 Clinical decision analysis indexes
- Chapter 17. Statistical assessment of diagnostic tests for the clinic
- Abstract
- 17.1 Detection capacity indexes
- 17.2 Diagnostic significance indexes
- Chapter 18. Systematic reviews and meta-analyses
- Abstract
- 18.1 Systematic review
- 18.2 Meta-analysis
- 18.3 Options if meta-analysis performance is not possible
- 18.4 Systematic review/meta-analysis limitations
- 18.5 Summary of systematic review/meta-analysis stages
- Chapter 19. Correlation and regression
- Abstract
- 19.1 Correlation
- 19.2 Regression
- 19.3 Multiple linear regression
- Chapter 20. Per-protocol analysis and intention-to-treat analysis
- Abstract
- 20.1 Per-protocol analysis
- 20.2 Intention-to-treat analysis
- Bibliography
- Suggested reading
- Appendix: Overview of study types for human health investigation
- Glossary
- Index
Product details
- No. of pages: 206
- Language: English
- Copyright: © Academic Press 2021
- Published: June 4, 2021
- Imprint: Academic Press
- Paperback ISBN: 9780323901024
- eBook ISBN: 9780323898973
About the Authors
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
Professor of Clinical Immunology, Carlos Chagas Institute of Medical Graduation; Professor and Chairman of Microbiology and Immunology, and Research Fellow, Teresopolis University Medical School - UNIFESO; Professor and Coordinator of the Genodermatoses Sector of the Clinical Genetics Service, Federal University of Rio de Janeiro, Brazil
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 University