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Principles of Biostatistics, Third Edition

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Authors:	Marcello Pagano, Kimberlee Gauvreau, and Heather Mattie
Publisher:	CRC Press
Copyright:	2022
ISBN-13:	978-0-367-35580-7
Pages:	604; hardcover

Authors:	Marcello Pagano, Kimberlee Gauvreau, and Heather Mattie
Publisher:	CRC Press
Copyright:	2022
ISBN-13:
Pages:	604; eBook

Authors:	Marcello Pagano, Kimberlee Gauvreau, and Heather Mattie
Publisher:	CRC Press
Copyright:	2022
ISBN-13:
Pages:	604; Kindle

Comment from the Stata technical group

The third edition of Principles of Biostatistics by Marcello Pagano, Kimberlee Gauvreau, and Heather Mattie continues to be a wonderful tool for biological and health science students and researchers. The book is divided into three parts: "Variability" (three chapters), "Probability" (four chapters), and "Inference" (fourteen chapters). No prior statistical knowledge is assumed, and basic college math is adequate to understand the occasional mathematical formulas in the text.

Many new topics have been introduced in the third edition, while other topics have been considerably improved and expanded. For instance, material covering screening and diagnostic tests has been given its own chapter. New sections on the Kruskal-Wallis test, the Cox proportional hazards model, and sample-size calculations for a two-sample test on means and proportions have been added. Given the importance of different study designs, a new chapter (the final one) highlights the different characterstics of study designs for randomized and observational studies. A 14-page glossary of definitions for statistical terms has been added to the end of the book as well. Each chapter now has summary boxes that include the relevant mathematical formulas for ease of reference. The new edition also expands the Review Exercises sections and continues to use real published datasets that are available here. Stata and R code for the computer output in the book are also provided.

View table of contents >>

1. Introduction

1.1 Why Study Biostatistics
1.2 Difficult Numbers
1.3 Overview of the Text

1.3.1 Part I: Chapters 2–4 Variability
1.3.2 Part II: Chapters 5–8 Probability
1.3.3 Part III: Chapters 9–22 Inference
1.3.4 Computing Resources

1.4 Review Exercises

I Variability

2. Descriptive Statistics

2.1 Types of Numerical Data

2.1.1 Nominal Data
2.1.2 Ordinal Data
2.1.3 Ranked Data
2.1.4 Discrete Data
2.1.5 Continuous Data

2.2 Tables

2.2.1 Frequency Distributions
2.2.2 Relative Frequency

2.3 Graphs

2.3.1 Bar Charts
2.3.2 Histograms
2.3.3 Frequency Polygons
2.3.4 Box Plots
2.3.5 Two-Way Scatter Plots
2.3.6 Line Graphs

2.4 Numerical Summary Measures

2.4.1 Mean
2.4.2 Median
2.4.3 Mode
2.4.3 Range
2.4.5 Interquartile Range
2.4.6 Variance and Standard Deviation

2.5 Empirical Rule
2.6 Further Applications
2.7 Review Applications

3. Rates and Standardization

3.1 Rates
3.2 Adjusted Rates

3.2.1 Direct Standardization
3.2.2 Indirect Standardization

3.3 Further Applications
3.4 Review Exercises

4. Life Tables

4.1 Historical Development
4.2 Life Table as a Predictor of Longevity
4.3 Mean Survival
4.4 Median Survival
4.5 Further Applications
4.6 Review Exercises

II Probability

5. Probability

5.1 Operations on Events and Probability
5.2 Conditional Probability
5.3 Total Probability Rule
5.4 Relative Risk and Odds Ratio
5.5 Further Applications
5.6 Review Exercises

6. Screening and Diagnostic Tests

6.1 Sensitivity and Specificity
6.2 Bayes' Theorem
6.3 Likelihood Ratios
6.4 ROC Curves
6.5 Calculation of Prevalence
6.6 Varying Sensitivty
6.7 Further Applications
6.8 Review Exercises

7. Theoretical Probability Distributions

7.1 Probability Distributions
7.2 Binomial Distribution
7.3 Poisson Distribution
7.4 Normal Distribution
7.5 Further Applications
7.6 Review Exercises

8. Sampling Distribution of the Mean

8.1 Sampling Distributions
8.2 Central Limit Theorem
8.3 Applications of the Central Limit Theorem
8.4 Further Applications
8.5 Review Exercises

III Inference

9. Confidence Intervals

9.1 Two-Sided Confidence Intervals
9.2 One-Sided Confidence Intervals
9.3 Student’s t Distribution
9.4 Further Applications
9.5 Review Exercises

10. Hypothesis Testing

10.1 General Concepts
10.2 Two-Sided Tests of Hypothesis
10.3 One-Sided Tests of Hypothesis
10.4 Types of Error
10.5 Power
10.6 Sample Size Estimation
10.7 Further Applications
10.8 Review Exercises

11. Comparison of Two Means

11.1 Paired Samples
11.2 Independent Samples

11.2.1 Equal Variances
11.2.2 Unequal Variances

11.3 Sample Size Estimation for Two Means
11.4 Further Applications
11.5 Review Exercises

12. Analysis of Variance

12.1 One-Way Analysis of Variance

12.1.1 The Problem
12.1.2 Sources of Variation

12.2 Multiple Comparisons Procedures
12.3 Further Applications
12.4 Review Exercises

13. Nonparametric Methods

13.1 Sign Test
13.2 Wilcoxon Signed-Rank Test
13.3 Wilcoxon Rank Sum Test
13.4 Kruskal-Wallis Test
13.5 Advantages and Disadvantages of Nonparametric Methods
13.6 Further Applications
13.7 Review Exercises

14. Inference on Proportions

14.1 Normal Approximation to the Binomial Distribution
14.2 Sampling Distribution of a Proportion
14.3 Confidence Intervals
14.4 Hypothesis Testing
14.5 Sample Size Estimation
14.6 Comparison of Two Proportions
14.7 Sample Size Estimation for Two Proportions
14.8 Further Applications
14.9 Review Exercises

15. Contingency Tables

15.1 The Chi-Square Test

15.1.1 2 x 2 Tables
15.1.2 r x c Tables

15.2 McNemar’s Test
15.3 The Odds Ratio
15.4 Berkson’s Fallacy
15.5 Further Applications
15.6 Review Exercises

16. Correlation

16.1 Two-Way Scatter Plot
16.2 Pearson Correlation Coefficient
16.3 Spearman Rank Correlation Coefficient
16.4 Further Applications
16.5 Review Exercises

17. Simple Linear Regression

17.1 Regression Concepts
17.2 The Model

17.2.1 Population Regression Line
17.2.2 Method of Least Squares
17.2.3 Inference for Regression Coefficients
17.2.4 Inference for Predicted Values

17.3 Evaluation of the Model

17.3.1 Coefficient of Determination
17.3.2 Residual Plots
17.3.3 Transformations

17.4 Further Applications
17.5 Review Exercises

18. Multiple Linear Regression

18.1 The Model

18.1.1 Least Squares Regression Equation
18.1.2 Inference for Regression Coefficients
18.1.3 Indicator Variables
18.1.4 Interaction Terms

18.2 Model Selection
18.3 Evaluation of the Model
18.4 Further Applications
18.5 Review Exercises

19. Logistic Regression

19.1 The Model

19.1.1 Logistic Function
19.1.2 Fitted Equation

19.2 Indicator Variables
19.3 Multiple Logistic Regression
19.4 Simpson's Paradox
19.5 Interaction Terms
19.6 Model Selection
19.7 Further Applications
19.8 Review Exercises

20. Survival Analysis

20.1 Life Table Method
20.2 Product-Limit Method
20.3 Log-Rank Test
20.4 Cox Proportional Hazards Model
20.5 Further Applications
20.6 Review Exercises

21. Sampling Theory

21.1 Sampling Designs

21.1.1 Simple Random Sampling
21.1.2 Systematic Sampling
21.1.3 Stratified Sampling
21.1.4 Cluster Sampling
21.1.5 Ratio Estimator
21.1.6 Two-Stage Cluster Sampling
21.1.7 Design Effect
21.1.8 Nonprobability Sampling

21.2 Sources of Bias
21.3 Further Applications
21.4 Review Exercises

22. Study Design

22.1 Randomized Studies

22.1.1 Control Groups
22.1.2 Randomization
22.1.3 Blinding
22.1.4 Intention to Treat
22.1.5 Crossover Trial
22.1.6 Equipoise

22.2 Observational Studies

22.2.1 Cross-Sectional Studies
22.2.2 Longitudinal Studies
22.2.3 Case-Control Studies
22.2.4 Cohort Studies
22.2.5 Consequences of Design Flaws

22.3 Big Data
22.4 Review Exercises

Bibliography

Glossary

Statistical Tables

Index

Principles of Biostatistics, Third Edition

Comment from the Stata technical group

Table of contents

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Principles of Biostatistics, Third Edition

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