Principles of Biostatistics 2nd Edition by Marcello Pagano, Kimberlee Gauvreau, Heather Mattie – Ebook PDF Instant Download/Delivery: 0367355807, 9780367355807
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ISBN 10: 0367355807
ISBN 13: 9780367355807
Author: Marcello Pagano, Kimberlee Gauvreau, Heather Mattie
Principles of Biostatistics, Third Edition is a concepts-based introduction to statistical procedures that prepares public health, medical, and life sciences students to conduct and evaluate research. With an engaging writing style and helpful graphics, the emphasis is on concepts over formulas or rote memorization. Throughout the book, the authors use practical, interesting examples with real data to bring the material to life. Thoroughly revised and updated, this third edition includes a new chapter introducing the basic principles of Study Design, as well as new sections on sample size calculations for two-sample tests on means and proportions, the Kruskal-Wallis test, and the Cox proportional hazards model. Key Features: Includes a new chapter on the basic principles of study design. Additional review exercises have been added to each chapter. Datasets and Stata and R code are available on the book’s website. The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them.
Principles of Biostatistics 2nd 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
2.4.4 Range
2.4.5 Interquartile Range
2.4.6 Variance and Standard Deviation
2.5 Empirical Rule
2.6 Further Applications
2.7 Review Exercises
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 Sensitivity
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 for One Proportion
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 Chi-Square Test
15.1.1 2 × 2 Tables
15.1.2 r × c Tables
15.2 McNemar’s Test
15.3 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
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