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Essentials of Biostatistics for Public Health 4th New edition [Minkštas viršelis]

3.20/5 (5 ratings by Goodreads)
  • Formatas: Paperback / softback, 400 pages, weight: 765 g
  • Išleidimo metai: 22-Jun-2022
  • Leidėjas: Jones and Bartlett Publishers, Inc
  • ISBN-10: 1284231976
  • ISBN-13: 9781284231977
Kitos knygos pagal šią temą:
Essentials of Biostatistics for Public Health 4th New editionDidesnis paveikslėlis
  • Formatas: Paperback / softback, 400 pages, weight: 765 g
  • Išleidimo metai: 22-Jun-2022
  • Leidėjas: Jones and Bartlett Publishers, Inc
  • ISBN-10: 1284231976
  • ISBN-13: 9781284231977
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781284231977.html
Raktažodžiai:
"Essentials of Biostatistics in Public Health, Fourth Edition provides a fundamental and engaging background for students learning to apply and appropriately interpret biostatistics applications in the field of public health. Many examples are drawn directly from the author's remarkable clinical experiences with the renowned Framingham Heart Study, making this text practical, interesting, and accessible for those with little mathematical background. The examples are real, relevant, and manageable in sizeso that students can easily focus on applications rather than become overwhelmed by computations.The Fourth Edition has been thoroughly updated, and now offers a new chapter on career opportunities and new case studies in each chapter focused on COVID-19. This edition will also include free access to JMP Student Edition Software, which is an easy-to-use version of SAS' statistical discovery software and is well-suited to for introductory or intermediate statistics courses. Key Features: Updated "in the news" features at the start of each chapter Additional problems for students to test their knowledge Revised instructor resources with suggestions for teaching biostatistics online Updated Excel Workbook - included in the ebook - provides hands-on experience with statistical computing using Microsoft Excel New JMP Student Edition Software - included for free download with purchase of the book or eBook - provides a streamlined, easy-to-use version of SAS' statistical discovery software New accompanying JMPworkbook - included in the eBook- provides exercises and examples of how to use JMP modeling and computing biostatistics"--

Essentials of Biostatistics in Public Health, Fourth Edition provides a fundamental and engaging background for students learning to apply and appropriately interpret biostatistics applications in the field of public health. Many examples are drawn directly from the author’s remarkable clinical experiences with the renowned Framingham Heart Study, making this text practical, interesting, and accessible for those with little mathematical background. The examples are real, relevant, and manageable in size so that students can easily focus on applications rather than become overwhelmed by computations.The Fourth Edition has been thoroughly updated, and now offers a new chapter on career opportunities and new case studies in each chapter focused on COVID-19. This edition will also include free access to JMP Student Subscription, which is a streamlined version of SAS’ statistical discovery software and is well-suited to for introductory or intermediate statistics courses.Key Features:- New cases based on COVID-19 highlight the importance and practical applications of COVID-19- New chapter on careers in biostatistics provides helpful guidance and insight to undergraduates choosing a career- Chapter opening "In the News Feature" raises key questions and highlights issues from the news/social media to engage students in thinking about the specific application about to be discussed in light of the important problems that impact people and health - Updated Excel Workbook – included in the ebook – provides hands-on experience with statistical computing using Microsoft Excel- New JMP Student Subscription – included for free download with purchase of the book or eBook – provides a student access to SAS’ statistical discovery software- New accompanying JMP workbook – included in the eBook– provides exercises and examples of how to use JMP modeling and computing biostatistics
The Essential Public Health Series x
Editor's Preface xiii
Author's Preface xv
Additional Materials Available Online xvii
Pedagogical Features xxi
Acknowledgments xxiii
About the Author xxv
Chapter 1 Introduction
1(6)
1.1 What Is Biostatistics?
2(1)
1.2 What Are The Issues?
2(3)
1.3 Summary
5(1)
References
6(1)
Chapter 2 Study Designs
7(18)
2.1 Vocabulary
8(1)
2.2 Observational Study Designs
9(5)
2.3 Randomized Study Designs
14(3)
2.4 The Framingham Heart Study
17(1)
2.5 More On Clinical Trials
17(4)
2.6 Sample Size Implications
21(1)
2.7 Summary
21(1)
2.8 Practice Problems
22(2)
References
24(1)
Chapter 3 Quantifying the Extent of Disease
25(16)
3.1 Prevalence
26(1)
3.2 Incidence
26(3)
3.3 Relationships Between Prevalence and Incidence
29(1)
3.4 Comparing the Extent of Disease Between Groups
29(3)
3.5 Summary
32(3)
3.6 Practice Problems
35(4)
References
39(2)
Chapter 4 Summarizing Data Collected in the Sample
41(28)
4.1 Dichotomous Variables
43(3)
4.2 Ordinal and Categorical Variables
46(6)
4.3 Continuous Variables
52(10)
4.4 Summary
62(3)
4.5 Practice Problems
65(3)
References
68(1)
Chapter 5 The Role of Probability
69(30)
5.1 Sampling
70(2)
5.2 Basic Concepts
72(1)
5.3 Conditional Probability
73(3)
5.4 Independence
76(1)
5.5 Bayes' Theorem
77(1)
5.6 Probability Models
78(14)
5.7 Summary
92(2)
5.8 Practice Problems
94(4)
References
98(1)
Chapter 6 Confidence Interval Estimates
99(26)
6.1 Introduction to Estimation
100(2)
6.2 Confidence Intervals for one Sample, Continuous Outcome
102(2)
6.3 Confidence Intervals for One Sample, Dichotomous Outcome
104(1)
6.4 Confidence Intervals for Two Independent Samples, Continuous Outcome
105(4)
6.5 Confidence Intervals for Matched Samples, Continuous Outcome
109(3)
6.6 Confidence Intervals for Two Independent Samples, Dichotomous Outcome
112(5)
6.7 Summary
117(2)
6.8 Practice Problems
119(4)
References
123(2)
Chapter 7 Hypothesis Testing Procedures
125(48)
7.1 Introduction to Hypothesis Testing
126(5)
7.2 Tests with One Sample, Continuous Outcome
131(3)
7.3 Tests with One Sample, Dichotomous Outcome
134(1)
7.4 Tests with One Sample, Categorical and Ordinal Outcomes
135(4)
7.5 Tests with Two Independent Samples, Continuous Outcome
139(3)
7.6 Tests with Matched Samples, Continuous Outcome
142(2)
7.7 Tests with Two Independent Samples, Dichotomous Outcome
144(4)
7.8 Tests with More than Two Independent Samples, Continuous Outcome
148(8)
7.9 Tests for Two or More Independent Samples, Categorical and Ordinal Outcomes
156(5)
7.10 Summary
161(2)
7.11 Practice Problems
163(7)
References
170(3)
Chapter 8 Power and Sample Size Determination
173(24)
8.1 Issues in Estimating Sample Size for Confidence Interval Estimates
174(7)
8.2 Issues in Estimating Sample Size for Hypothesis Testing
181(9)
8.3 Summary
190(2)
8.4 Practice Problems
192(3)
References
195(2)
Chapter 9 Multivariable Methods
197(32)
9.1 Confounding and Effect Modification
199(5)
9.2 The Cochran--Mantel--Haenszel Method
204(2)
9.3 Introduction to Correlation and Regression Analysis
206(6)
9.4 Multiple Linear Regression Analysis
212(5)
9.5 Multiple Logistic Regression Analysis
217(3)
9.6 Summary
220(1)
9.7 Practice Problems
221(5)
References
226(3)
Chapter 10 Nonparametric Tests
229(26)
10.1 Introduction to Nonparametric Testing
231(2)
10.2 Tests with Two Independent Samples
233(5)
10.3 Tests with Matched Samples
238(9)
10.4 Tests with More Than Two Independent Samples
247(4)
10.5 Summary
251(1)
10.6 Practice Problems
252(2)
References
254(1)
Chapter 11 Survival Analysis
255(28)
11.1 Introduction to Survival Data
257(1)
11.2 Estimating the Survival Function
258(6)
11.3 Comparing Survival Curves
264(5)
11.4 Cox Proportional Hazards Regression Analysis
269(4)
11.5 Extensions
273(1)
11.6 Summary
274(2)
11.7 Practice Problems
276(5)
References
281(2)
Chapter 12 Data Visualization
283(48)
12.1 Design Principles
284(2)
12.2 When and How to Use Text, Tables, and Figures
286(3)
12.3 Presenting Data and Statistical Results In Tables
289(10)
12.4 Presenting Data and Statistical Results in Figures
299(22)
12.5 Summary
321(3)
12.6 Practice Problems
324(4)
References
328(3)
Chapter 13 Careers in Biostatistics
331(10)
13.1 What Biostatisticians Do
332(3)
13.2 Industries and Sectors
335(2)
13.3 Job Outlook, Job Satisfaction
337(1)
13.4 Training, Skills, and Opportunities
337(1)
13.5 Summary
338(1)
References
339(2)
Appendix 341(18)
Glossary 359(10)
Index 369
'Lisa M. Sullivan, PhD, is the associate dean for education, professor and former chair of biostatistics at the Boston University School of Public Health.' Her scholarship is in development and evaluation of risk prediction models mainly for a range of cardiovascular outcomes in the Framingham Heart Study and include the risk functions for coronary heart disease which featured prominently in the National Cholesterol Education Programs Adult Treatment Panel III.' She also has experience with randomized clinical trials and large, international observational studies of the effects of various exposures and treatments on adverse outcomes of pregnancy.' She has published over 220 scientific journal articles and several book chapters on these topics.' She is author of Essentials of Biostatistics in Public Health, currently in it 3rd edition.' She is also co-author of Introductory Applied Biostatistics, co-editor of Teaching Public Health, and was co-editor-in-chief of the Encyclopedia of Clinical Trials.' Sullivan was the Principal Investigator for the Boston University Summer Institute for Training in Biostatistics, continuously funded since 2004, designed to interest undergraduates in the field of biostatistics.' She is also the former Co-Director of the Graduate Program in Biostatistics at Boston University.' Sullivan has won numerous awards for excellence in teaching both at the undergraduate and graduate levels, including the Norman A. Scotch Award for Excellence in Teaching which is presented annually to an individual who has made outstanding and sustained contributions to the education program at Boston University School of Public Health. She was awarded the prestigious Metcalf Award for Excellence in Teaching at Boston University and also the ASPH/Pfizer Award for Teaching Excellence - an award given annually to the outstanding teacher in accredited schools of public health in North America.' She also received the Outstanding Teaching Award from the Section on Teaching Statistics in the Health Sciences of the American Statistical Association, the Massachusetts ACE National Network of Women Leaders Leadership Award and the Mosteller Statistician of the Year award presented by the Boston Chapter of the American Statistical Association.