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E-raamat: Practical Biostatistics: A Friendly Step-by-Step Approach for Evidence-based Medicine

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(Carlos Chagas Institute of Medical Graduation; Teresopolis University Medical School - UNIFESO; Genodermatoses Sector of the Clinical Genetics Service, Federal University of Rio de Janeiro, Brazil), (MD degree, Teresopolis University Me)
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  • Ilmumisaeg: 26-Jul-2012
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780124158573
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Practical Biostatistics: A Friendly Step-by-Step Approach for Evidence-based MedicineSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 26-Jul-2012
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780124158573
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Mendel Suchmacher and Mauro Geller (both clinical immunology, Carlos Chagas Institute of Medical Post-graduation, Rio de Janeiro) share the lessons they have learned over several years assimilating mathematical concepts through biostatistics-specialized literature, personal guidance, and reading clinical trials. They write for clinicians who, like them, are not trained biostatisticians, but need to know enough to evaluate reports and sometimes generate their own. They did, however, have a biostatician review the material, just to be sure. Their choice of a common database program is intended as a bridge between biostatistics and the common technology user. Academic Press is an imprint of Elsevier. Annotation ©2012 Book News, Inc., Portland, OR (booknews.com)



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

Arvustused

"...strongly recommended as a practical guide for readers interested in applied biostatistics. Each chapter of the book is accompanied by practical examples and a huge set of reflection questions and answers." --Zentralblatt MATH, Practical 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." --Doody.com, April 2013

"Practical Biostatistics is destined to be a companion book for health professionals and graduation students who face the challenge of assimilating concepts on statistics." --Mauri Carakushansky, MD, Pediatric Endocrinologist - Nemours Children's Clinic Orlando, Assistant Professor of Pediatrics - Florida State University, Assistant Professor of Pediatrics - University of Central Florida

"This work by Dr. Suchmacher and Dr. Geller is bound to become a classic and should be readily available on the desk, shelf and on line." --Salin Dahlben, Harvard University, Clinical Assistant Professor in Psychiatry, Tufts University

"Dr. Suchmacher and Dr. Geller are experienced researchers and writers in the clinical research field, who were able to fathom the often confusing realm of Statistics applied to biological sciences, and to come back with a pragmatic study proposal for interested medical students and healthcare professionals [ ] In my opinion, 'Practical Biostatistics' will undoubtedly be welcomed as one of the books designed to bring medical students and healthcare professionals alike, closer to a better understanding of this inescapable issue." --Spyros G.E. Mezitis, Assistant Professor of Clinical Medicine, The New York Presbyterian Hospital Weill, Cornell Medical Center

"I believe the result of [ Drs. Suchmacher and Gellers] efforts will prove useful for many medical students and researchers, who must thrive in an era when Biostatistics is destined to be an ever present matter." --Allan E. Rubenstein, Clinical Professor of Neurology, The Stephen D. Hassenfeld Children's Center for Cancer and Blood Disorders, Langone Medical Center, School of Medicine, New York University

"Practical Biostatistics is destined to be a companion book for health professionals and graduation students who face the challenge of assimilating concepts on statistics." --Mauri Carakushansky, MD, Pediatric Endocrinologist - Nemours Children's Clinic Orlando, Assistant Professor of Pediatrics - Florida State University, Assistant Professor of Pediatrics - University of Central Florida

Muu info

A concise guide for the interpretation and writing of observational studies and clinical trials
Foreword ix
Preface xi
Acknowledgments xii
Part I Introduction
1 Study Type Determination
3(10)
1.1 Epidemiological Studies
3(1)
1.1.1 Ecological Studies
3(1)
1.1.2 Cross-Sectional Studies
3(1)
1.1.3 Longitudinal Studies
4(1)
1.2 Analytical Studies
4(7)
1.2.1 Observational Studies
4(3)
1.2.2 Intervention Studies
7(4)
1.3 Summary of Study Types
11(2)
Part I Reader Resources: Self-evaluation, Annotated Answers, Suggested Reading
13(6)
Part II Observational Studies
2 Determination of Association Strength between an Exposure Factor and an Event in Observational Studies
19(12)
2.1 Case-Control Studies
19(6)
2.1.1 Odds Ratio
19(3)
2.1.2 Number Needed to Harm
22(1)
2.1.3 Summary
23(2)
2.2 Cohort Studies
25(6)
2.2.1 Relative Risk
25(3)
2.2.2 Number Needed to Harm
28(1)
2.2.3 Summary
29(2)
3 Increasing Accuracy in Observational Studies
31(5)
3.1 Stratified Analysis
31(3)
3.1.1 Example 1
31(2)
3.1.2 Example 2
33(1)
3.2 Multivariable Analysis
34(2)
Part II Reader Resources: Self-evaluation, Annotated Answers, Suggested Reading
36(7)
Part III Step-by-Step Biostatistics of a Clinical Trial
4 Step 1: Investigator's Hypothesis and Expression of its Corresponding Outcome
43(4)
5 Step 2: n Estimation and n Assessment of a Published Trial
47(12)
5.1 Factors Influencing n Determination
47(3)
5.1.1 Empirical Factors
47(1)
5.1.2 Mathematical Factors
48(2)
5.2 n Calculation
50(5)
5.2.1 For Studies Aiming to Analyze Differences Between Means
51(2)
5.2.2 For Studies Aiming to Analyze Differences Between Proportions
53(2)
5.3 Assessing n of a Published Trial
55(4)
5.3.1 Studies that Analyzed Differences Between Means
55(1)
5.3.2 Studies that Analyzed Differences Between Proportions
56(3)
6 Step 3: Organization of Variables and Endpoints
59(4)
6.1 Qualitative Variables
59(1)
6.1.1 Categorical
59(1)
6.1.2 Ordinal
59(1)
6.2 Quantitative Variables
60(3)
6.2.1 Discrete
60(1)
6.2.2 Continuous
60(3)
7 Step 4: Measures for Results Expression of a Clinical Trial
63(28)
7.1 Central Tendency Measures
63(3)
7.1.1 Mean
63(1)
7.1.2 Median
64(2)
7.1.3 Mode
66(1)
7.2 Dispersal Measures
66(5)
7.2.1 Amplitude
66(1)
7.2.2 Variance and Standard Deviation
66(3)
7.2.3 Coefficient of Variation
69(1)
7.2.4 Standard Error of the Mean
70(1)
7.3 Position Measures: Quantiles
71(4)
Appendix 7.1: How to Calculate Mean Using Microsoft Excel (Section 7.1.1)
75(2)
Appendix 7.2: How to "Trim" The Mean of Outliers (Section 7.1.1)
77(2)
Appendix 7.3: How to Determine Median Using Microsoft Excel (Section 7.1.2)
79(2)
Appendix 7.4: How to Determine Mode Using Microsoft Excel (Section 7.1.3)
81(2)
Appendix 7.5: How to Calculate Standard Deviation Using Microsoft Excel (Section 7.2.2)
83(2)
Appendix 7.6: How to Find the Exact BMI that Corresponds to the 90th Percentile Using Microsoft Excel (Section 7.3)
85(2)
Appendix 7.7: How to Put all BM's in a "Rank and Percentile" Perspective Using Microsoft Excel (Section 7.3)
87(4)
8 Step 5: Determination of Normality or Non-Normality of Data Distribution
91(14)
Appendix 8.1: How to Verify Normality of a Graph Curve Using Microsoft Excel
97(8)
9 Step 6: Hypothesis Testing
105(12)
9.1 Parametric Tests for Independent and Dependent Samples
108(3)
9.1.1 Student's t Test
108(1)
9.1.2 Paired Student's t Test
109(2)
9.2 Nonparametric Tests
111(6)
9.2.1 For Independent Samples
111(3)
9.2.2 For Dependent Samples: Wilcoxon Signed-Rank Test
114(3)
10 Step 7: Correlating Sample Data with the General Population - 95% Confidence Interval
117(12)
10.1 Point Estimation
118(3)
10.1.1 Sampling Distribution of the Mean and the Sampling Mean
118(1)
10.1.2 Standard Error
119(1)
10.1.3 Standard Error of the Mean
120(1)
10.2 Interval Estimation (95% Confidence Interval)
121(5)
Appendix 10.1: How to Determine Confidence Intervals Using Microsoft Excel (Sample A)
126(3)
Part III Reader Resources: Self-evaluation, Annotated Answers, Suggested Reading
129(10)
Part IV Additional Concepts in Biostatistics
11 Individual and Collective Benefit and Risk Indexes Inferable from Intervention Studies
139(14)
11.1 Treatment Effect Indexes
139(10)
11.1.1 Risk Indexes
139(7)
11.1.2 Benefit Indexes
146(1)
11.1.3 Number Needed to Treat
147(1)
11.1.4 Number Needed to Harm
148(1)
11.1.5 Likelihood of Being Helped Versus Being Harmed
148(1)
11.2 Clinical Decision Analysis Indexes
149(4)
11.2.1 Patient-Specific Number Needed to Treat
149(1)
11.2.2 Patient-Specific Number Needed to Harm
150(1)
11.2.3 Patient-Specific Likelihood of Being Helped Versus Being Harmed
151(2)
12 Statistical Assessment of Diagnostic Tests for the Clinic
153(6)
12.1 Detection Capacity Indexes
153(2)
12.1.1 Sensitivity
154(1)
12.1.2 Specificity
154(1)
12.1.3 Likelihood Ratio
154(1)
12.2 Diagnostic Significance Indexes
155(4)
12.2.1 Pretest Probability (Prevalence)
155(1)
12.2.2 Pretest Odds
156(1)
12.2.3 Post-Test Odds
156(1)
12.2.4 Post-Test Probability
156(1)
12.2.5 Positive Predictive Value
156(1)
12.2.6 Negative Predictive Value
157(2)
13 Systematic Reviews and Meta-Analyses
159(8)
13.1 Definitions
159(1)
13.2 Systematic Review
159(1)
13.2.1 Problem Formulation
159(1)
13.2.2 Primary Studies Search and Selection
159(1)
13.2.3 Primary Studies Data Extraction
160(1)
13.3 Meta-Analysis
160(4)
13.3.1 Publication Bias Detection
161(1)
13.3.2 Heterogeneity Analysis
161(1)
13.3.3 Summarized Statistical Determination
162(1)
13.3.4 Meta-Analysis Performance and Expression
162(2)
13.4 Options if Meta-Analysis Performance is not Advisable
164(1)
13.5 Systematic Review/Meta-Analysis Limitations
165(1)
13.6 Systematic Review/Meta-Analysis Stages Summary
165(1)
13.7 Suggested Resources and Literary Sources
166(1)
14 Correlation and Regression
167(20)
14.1 Correlation
167(3)
14.2 Regression
170(2)
14.3 Multiple Linear Regression
172(3)
Appendix 14.1: How to Build a Scatterplot and to Add a Trend Line Using Microsoft Excel
175(8)
Appendix 14.2: How to Calculate Pearson's Correlation Coefficient Using Microsoft Excel
183(2)
Appendix 14.3: How to Predict a Dependent Variable Using Microsoft Excel
185(2)
15 Per Protocol Analysis and Intention to Treat Analysis
187(4)
Part IV Reader Resources: Self-evaluation, Annotated Answers, Suggested Reading
191(8)
Appendix Microsoft Excel 2010 Basics
A.1 Structure and Main Features of a Microsoft Excel 2010 Worksheet
199(3)
A.2 Location of Statistical Resources
202(4)
A.3 Building a Plain Table
206(2)
A.4 Building a Basic Chart
208(1)
A.5 Building a Chart Out of a Table
209(8)
A.6 Pivot Table
217(3)
Suggested Reading
220(1)
Glossary 221(6)
Index 227
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. 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.
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