Biostatistics for the Health Sciences
Published on 5. February 2007
Book
Paperback/Softback
552 pages
978-0-13-117660-7 (ISBN)
Description
This book provides a solid foundation in introductory biostatistics with up-to-date methods, lucid explanations, and a modern approach. KEY TOPICS: Explains commonly used biostatistical methods, such as odds and risk ratios, and Fisher's exact test, in a clear and thorough manner. Introduces equivalence testing in a variety of research settings. Presents nonparametric methods in a modern light, couched in the broader context of permutation-based methods. Provides real-world data with case studies consisting of synopses of published research. Provides step-by-step solutions to exercises, along with pertinent equations used in obtaining the solution and page numbers of relevant discussions. MARKET: For health science students and professionals who need to increase their understanding of biostatistics.
More details
Persons
Clifford (Cliff) Blair is Professor Emeritus and former interim chair of the Department of Epidemiology and Biostatistics in the College of Public Health at the University of South Florida. He has also held faculty positions in the Colleges of Medicine and Education at the same university. He was coordinator of Measurement and Research at The Johns Hopkins University. He is author or co-author of 70 articles appearing in refereed journals of which 44 appeared in statistics or statistics related journals, 21 in medical research journals (including The New England Journal of Medicine), and five in other research oriented journals. He has authored two book chapters. He received the Public Health Student Association Distinguished Teacher Award in the academic year 1995-1996 and again in 1998-1999. He also received the University of South Florida Teaching Incentive Program Outstanding Teacher Award in 1996-1997. His research earned him the Distinguished Researcher Award, presented by the Florida Educational Research Association in 1986.
Dr. Richard A. Taylor, Centers for Disease Control and Prevention, Coordinating Office for Terrorism Preparedness and Emergency Response
Dr. Richard A. Taylor, Centers for Disease Control and Prevention, Coordinating Office for Terrorism Preparedness and Emergency Response
Content
1. Foundations of Biostatistics
1.1 Introduction
1.2 Populations and Samples
1.3 Parameters and Statistics
1.4 Descriptive and Inferential Statistics
1.5 Why Populations and Samples?
1.6 What Happens Now?
Key Words and Phrases
Exercises
2. Descriptive Methods
2.1 Introduction
2.2 Sacles of Measurement
2.3 Summation Notation
2.4 Distributions
2.5 Graphs
2.6 Numerical Methods
2.7 A Re-Orientation
Key Words and Phrases
Exercises
3. Probability
3.1 Introduction
3.2 A Definition of Probability
3.3 Contingency Tables
3.4 The Normal Curve
Key Words and Phrases
Exercises
4. Introduction To Inference And One Sample Methods
4.1 Introduction
4.2 Sampling Distributions
4.3 Hypothesis Testing
4.4 Confidence Intervals
4.5 Comparison of Hypothesis Tests and Confidence Intervals
4.6 A Re-Orientation
Key Words and Phrases
Exercises
5. Paired Samples Methods
5.1 Introduction
5.2 Methods Related to Mean Difference
5.3 Methods Related to Proportions
5.4 Methods Related to Paired Samples Risk Ratios
5.5 Methods Related to Paired Samples Odds Ratios
Key Words and Phrases
Exercises
6. Two Independent Samples Methods
6.1 Introduction
6.2 Methods Related to Differences Between Means
6.3 Methods Related to Proportions
6.4 Methods Related to Independent Samples Risk Ratios
6.5 Methods Related to Independent Samples Odds Ratios
Key Words and Phrases
Exercises
7. Multi-Sample Methods
7.1 Introduction
7.2 The Oneway Analysis of Variance (ANOVA) F Test
7.3 The 2 By k Chi-Square Test
7.4 Multiple Comparison Procedures
Key Words and Phrases
Exercises
8. The Assessment of Relationships
8.1 Background
8.2 The Pearson Product-Moment Correlation Coefficient
8.3 The Chi-Square Test For Independence
Key Words and Phrases
Exercises
9. Linear Regression
9.1 Background
9.2 Simple Linear Regression
9.3 Multiple Linear Regression
9.4 Assumptions
9.5 Some Additional Comments Regarding the Utility of MLR
Key Words and Phrases
Exercises
10. Methods Based on The Permutation Principle
10.1 Introduction
10.2 Some Preliminaries
10.3 Applications
10.4 Further Comments Regarding Permutation Based Methods
Key Words and Phrases
Exercises
1.1 Introduction
1.2 Populations and Samples
1.3 Parameters and Statistics
1.4 Descriptive and Inferential Statistics
1.5 Why Populations and Samples?
1.6 What Happens Now?
Key Words and Phrases
Exercises
2. Descriptive Methods
2.1 Introduction
2.2 Sacles of Measurement
2.3 Summation Notation
2.4 Distributions
2.5 Graphs
2.6 Numerical Methods
2.7 A Re-Orientation
Key Words and Phrases
Exercises
3. Probability
3.1 Introduction
3.2 A Definition of Probability
3.3 Contingency Tables
3.4 The Normal Curve
Key Words and Phrases
Exercises
4. Introduction To Inference And One Sample Methods
4.1 Introduction
4.2 Sampling Distributions
4.3 Hypothesis Testing
4.4 Confidence Intervals
4.5 Comparison of Hypothesis Tests and Confidence Intervals
4.6 A Re-Orientation
Key Words and Phrases
Exercises
5. Paired Samples Methods
5.1 Introduction
5.2 Methods Related to Mean Difference
5.3 Methods Related to Proportions
5.4 Methods Related to Paired Samples Risk Ratios
5.5 Methods Related to Paired Samples Odds Ratios
Key Words and Phrases
Exercises
6. Two Independent Samples Methods
6.1 Introduction
6.2 Methods Related to Differences Between Means
6.3 Methods Related to Proportions
6.4 Methods Related to Independent Samples Risk Ratios
6.5 Methods Related to Independent Samples Odds Ratios
Key Words and Phrases
Exercises
7. Multi-Sample Methods
7.1 Introduction
7.2 The Oneway Analysis of Variance (ANOVA) F Test
7.3 The 2 By k Chi-Square Test
7.4 Multiple Comparison Procedures
Key Words and Phrases
Exercises
8. The Assessment of Relationships
8.1 Background
8.2 The Pearson Product-Moment Correlation Coefficient
8.3 The Chi-Square Test For Independence
Key Words and Phrases
Exercises
9. Linear Regression
9.1 Background
9.2 Simple Linear Regression
9.3 Multiple Linear Regression
9.4 Assumptions
9.5 Some Additional Comments Regarding the Utility of MLR
Key Words and Phrases
Exercises
10. Methods Based on The Permutation Principle
10.1 Introduction
10.2 Some Preliminaries
10.3 Applications
10.4 Further Comments Regarding Permutation Based Methods
Key Words and Phrases
Exercises