**Preface**

**Review of Topics in Probability and Statistics**

Introduction to Probability

Conditional Probability

Random Variables

The Uniform distribution

The Normal distribution

The Binomial Distribution

The Poisson Distribution

The Chi–Squared Distribution

Student’s *t*–distribution

The F-distribution

The Hypergeometric Distribution

The Exponential Distribution

Exercises

**Use of Simulation Techniques**

Introduction

What can we accomplish with simulations?

How to employ a simple simulation strategy

Generation of Pseudorandom Numbers

Generating Discrete and Continuous random variables

Testing Random Number Generators

A Brief Note on the Efficiency of Simulation Algorithms

Exercises

**The Central Limit Theorem**

Introduction

The Strong Law of Large Numbers

The Central Limit Theorem

Summary of the Inferential Properties of the Sample Mean

Appendix: Program Listings

Exercises

**Correlation and Regression**

Introduction

Pearson’s Correlation Coefficient

Simple Linear Regression

Multiple Regression

Visualization of Data

Model Assessment and Related Topics

Polynomial Regression

Smoothing Techniques

Appendix: A Short Tutorial in Matrix Algebra

Exercises

**Analysis of Variance**

Introduction

One–Way Analysis of Variance

General Contrast

Multiple Comparisons Procedures

Gabriel’s method

Dunnett’s Procedure

Two-Way Analysis of Variance: Factorial Design

Two-Way Analysis of Variance: Randomized Complete Blocks

Analysis of Covariance

Exercises

**DiscreteMeasures of Risk**

Introduction

Odds Ratio (OR) and Relative Risk (RR)

Calculating risk in the presence of confounding

Logistic Regression

Using SAS and *R *for Logistic Regression

Comparison of Proportions for Paired Data

Exercises

**Multivariate Analysis**

The Multivariate Normal Distribution

One and Two Sample Multivariate Inference

Multivariate Analysis of Variance

Multivariate Regression Analysis

Classification Methods

Exercises

**Analysis of Repeated Measures Data**

Introduction

Plotting Repeated Measures Data

Univariate Approaches for the Analysis of Repeated Measures Data

Covariance Pattern Models

Multivariate Approaches

Modern Approaches for the Analysis of Repeated Measures Data

Analysis of Incomplete Repeated Measures Data

Exercises

**NonparametricMethods**

Introduction

Comparing Paired Distributions

Comparing Two Independent Distributions

Kruskal–Wallis Test

Spearman’s rho

The Bootstrap

Exercises

**Analysis of Time to Event Data**

Incidence Density (ID)

Introduction to Survival Analysis

Estimation of the Survival Curve

Estimating the Hazard Function

Comparing Survival in Two Groups

Cox Proportional Hazards Model

Cumulative Incidence

Exercises

**Sample size and power calculations**

Sample sizes and power for tests of normally distributed data

Sample size and power for Repeated Measures Data

Sample size and power for survival analysis

Constructing Power Curves

Exercises

**Appendix A: Using SAS**

Introduction

Data input in SAS

Some Graphical Procdures: PROC PLOT and PROC CHART

Some Simple Data Analysis Procedures

Diagnosing errors in SAS programs

Exercises

**Appendix B: Using R**

Introduction

Getting started

Input/Output

Some Simple Data Analysis Procedures

Using *R *for plots

Comparing an R–session to a SAS session

Diagnosing problems in *R *programs

Exercises

**References**

**Index **