Essentials of Biostatistics in Public Health (Essential Public Health)

Essentials of Biostatistics in Public Health, Third 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 Third Edition offers a new chapter on data visualization and interpretation including guidance on reporting statistical results in tables, figures and text. Examples of well-organized, detailed and appropriately formatted tables and figures are provided along with samples of how best to interpret them. Examples of poorly organized tables and figures are also included to illustrate common misinterpretations of results, due in part to lack of clarity in presentation.The text comes packaged with an access code card that gives your students access to an online workbook for statistical computing using Microsoft Excel. The online workbook is available in both Mac and PC versions.Updates to the Third Edition:• New chapter on data visualization and interpretation• New "When and Why" sections in each chapter include timely examples of important medical and public health applications of biostatistical techniques to help students connect the technical aspects of how specific analyses are conducted to real and relevant applications. New suggestions for instructors to facilitate in-class discussions around these applications and their interpretation are included in the instructor resources• New examples from widely publicized clinical trials and from relevant and timely studies added throughout.• New integrative exercises included in the instructor resources that allow students to practice biostatistical analysis with real data using Excel.• New link to a publicly available, longitudinal dataset containing data collected in the Framingham Heart Study Cover Essentials of Biostatistics in Public Health Copyright Contents Acknowledgments Preface Prologue About the Author Chapter 1 Introduction 1.1 What Is Biostatistics? 1.2 What Are the Issues? 1.3 Summary Chapter 2 Study Designs 2.1 Vocabulary 2.2 Observational Study Designs 2.3 Randomized Study Designs 2.4 The Framingham Heart Study 2.5 More on Clinical Trials 2.6 Sample Size Implications 2.7 Summary 2.8 Practice Problems Chapter 3 Quantifying the Extent of Disease 3.1 Prevalence 3.2 Incidence 3.3 Relationships Between Prevalence and Incidence 3.4 Comparing the Extent of Disease Between Groups 3.5 Summary 3.6 Practice Problems Chapter 4 Summarizing Data Collected in the Sample 4.1 Dichotomous Variables 4.2 Ordinal and Categorical Variables 4.3 Continuous Variables 4.4 Summary 4.5 Practice Problems Chapter 5 The Role of Probability 5.1 Sampling 5.2 Basic Concepts 5.3 Conditional Probability 5.4 Independence 5.5 Bayes’ Theorem 5.6 Probability Models 5.7 Summary 5.8 Practice Problems Chapter 6 Confidence Interval Estimates 6.1 Introduction to Estimation 6.2 Confidence Intervals for One Sample, Continuous Outcome 6.3 Confidence Intervals for One Sample, Dichotomous Outcome 6.4 Confidence Intervals for Two Independent Samples, Continuous Outcome 6.5 Confidence Intervals for Matched Samples, Continuous Outcome 6.6 Confidence Intervals for Two Independent Samples, Dichotomous Outcome 6.7 Summary 6.8 Practice Problems Chapter 7 Hypothesis Testing Procedures 7.1 Introduction to Hypothesis Testing 7.2 Tests with One Sample, Continuous Outcome 7.3 Tests with One Sample, Dichotomous Outcome 7.4 Tests with One Sample, Categorical and Ordinal Outcomes 7.5 Tests with Two Independent Samples, Continuous Outcome 7.6 Tests with Matched Samples, Continuous Outcome 7.7 Tests with Two Independent Samples, Dichotomous Outcome 7.8 Tests with More Than Two Independent Samples, Continuous Outcome 7.9 Tests for Two or More Independent Samples, Categorical and Ordinal Outcomes 7.10 Summary 7.11 Practice Problems Chapter 8 Power and Sample Size Determination 8.1 Issues in Estimating Sample Size for Confidence Intervals Estimates 8.2 Issues in Estimating Sample Size for Hypothesis Testing 8.3 Summary 8.4 Practice Problems Chapter 9 Multivariable Methods 9.1 Confounding and Effect Modification 9.2 The Cochran–Mantel–Haenszel Method 9.3 Introduction to Correlation and Regression Analysis 9.4 Multiple Linear Regression Analysis 9.5 Multiple Logistic Regression Analysis 9.6 Summary 9.7 Practice Problems Chapter 10 Nonparametric Tests 10.1 Introduction to Nonparametric Testing 10.2 Tests with Two Independent Samples 10.3 Tests with Matched Samples 10.4 Tests with More Than Two Independent Samples 10.5 Summary 10.6 Practice Problems Chapter 11 Survival Analysis 11.1 Introduction to Survival Data 11.2 Estimating the Survival Function 11.3 Comparing Survival Curves 11.4 Cox Proportional Hazards Regression Analysis 11.5 Extensions 11.6 Summary 11.7 Practice Problems Chapter 12 Data Visualization 12.1 Design Principles 12.2 When and How to Use Text, Tables, and Figures 12.3 Presenting Data and Statistical Results in Tables 12.4 Presenting Data and Statistical Results in Figures 12.5 Summary 12.6 Practice Problems Appendix Glossary Index "Essentials of Biostatistics in Public Health, Third 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 Third Edition offers a new chapter on data visualization and interpretation including guidance on reporting statistical results in tables, figures and text. Examples of well-organized, detailed and appropriately formatted tables and figures are provided along with samples of how best to interpret them. Examples of poorly organized tables and figures are also included to illustrate common misinterpretations of results, due in part to lack of clarity in presentation"-- Provided by publisher