1. Introduction
1.1 What is Biostatistics?
1.2 What are the Issues?
1.3 Summary
2. Study Designs
2.1 Vocabulary
2.2 Observational Study Designs
2.2.1 The Case Report/Case Series
2.2.2 The Cross-Sectional Survey
2.2.3 The Cohort Study
2.2.4 The Case-Control Study
2.2.5 The Nested Case-Control Study
2.3 Experimental Study Designs
2.3.1 The Randomized Controlled Trial (RCT) or Clinical Trial
2.3.2 The Crossover Trial
2.4 The FraminghamHeart Study
2.5 More on Clinical Trials
2.6 Sample Size Implications
2.7 Summary
2.8 Practice Problems
3. Quantifying the Extent of Disease
3.1 Prevalence
3.2 Incidence
3.2.1 Problems Estimating Cumulative Incidence
3.2.2 Person-Time Data
3.2.3 Incidence Rate
3.3 Relationship Between Prevalence and Incidence
3.4 Comparing the Extent of Disease Between Groups
3.4.1 Risk Difference, Attributable Risk
3.4.2 Risk Ratio, Relative Risk, Odds Ratio, Rate Ratio
3.4.2.1 Issues with Person-Time Data
3.5 Summary
3.6 Practice Problems
4. Summarizing Data Collected in the Sample
4.1 Dichotomous Variables
4.1.1 Descriptive Statistics for Dichotomous Variables
4.1.2 Bar Charts for Dichotomous Variables
4.2 Ordinal and Categorical Variables
4.2.1 Descriptive Statistics for Ordinal and Categorical Variables
4.2.2 Histograms for Ordinal Variables
4.2.3 Bar Charts for Categorical Variables
4.3 Continuous Variables
4.3.1 Descriptive Statistics for Continuous Variables
4.3.2 Box-Whisker Plots for Continuous Variables
4.4 Summary
4.5 Practice Problems
5. The Role of Probability
5.1 Sampling
5.2 Basic Concepts
5.3 Conditional Probability
5.3.1 Evaluating Screening Tests
5.3.2 Sensitivity and Specificity
5.3.3 Positive and Negative Predictive Value
5.4 Independence
5.5 Bayes Theorem
5.6 Probability Models
5.6.1 A Probability Model for a Discrete Outcome: The Binomial Distribution
5.6.2 A Probability Model for a Continuous Outcome: The Normal Distribution
5.6.3 Sampling Distributions
5.7 Summary
5.8 Practice Problems
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
6.6.1 Confidence Intervals for the Risk Difference
6.6.2 Confidence Intervals for the Relative Risk
6.6.1 Confidence Intervals for the Odds Ratio
6.7 Chapter Summary
6.8 Practice Problems
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 Test with One Sample, Discrete Outcome
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 (Risk Difference, Relative Risk, Odds Ratio)
7.8 Tests with More Independent Samples, Continuous Outcome
7.9 Tests with Two or More Independent Samples, Discrete Outcome
7.10 Summary
7.11 Practice Problems
8. Power and Sample Size Determination
8.1 Issues in Estimating Sample Size for Confidence Intervals Estimates
8.1.1 Sample Size for One Sample, Continuous Outcome
8.1.2 Sample Size for One Sample, Dichotomous Outcome
8.1.3 Sample Sizes for Two Independent Samples, Continuous Outcome
8.1.4 Sample Size for Matched Samples, Continuous Outcome
8.1.5 Sample Sizes for Two Independent Samples, Dichotomous Outcome
8.2 Issues in Estimating Sample Size for Hypothesis Testing
8.2.1 Sample Size for One Sample, Continuous Outcome
8.2.2 Sample Size for One Sample, Dichotomous Outcome
8.2.3 Sample Sizes for Two Independent Samples, Continuous Outcome
8.2.4 Sample Size for Matched Samples, Continuous Outcome
8.2.5 Sample Sizes for Two Independent Samples, Dichotomous Outcome
8.3 Summary
8.4 Practice Problems
9. Multivariable Methods
9.1 Confounding and Effect Modification
9.2 Cochran-Mantel-Haenszel Test
9.3 Introduction to Regression Analysis
9.4 Multiple Linear Regression Analysis
9.5 Multiple Logistic Regression Analysis
9.6 Summary
9.7 Practice Problems
Workbook(s)
Student solutions manual
Statistical computing using MS Excel
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