Bootstrap Methods: A Guide for Practitioners and Researchers

1. What is bootstrapping? -- 1.1. Background -- 1.2. Introduction -- 1.3. Wide range of applications -- 1.4. Historical notes -- 1.5. Summary -- 2. Estimation -- 2.1. Estimating bias -- 2.1.1. How to do it by bootstrapping -- 2.1.2. Error rate estimation in discrimination -- 2.1.3. Error rate estimation: an illustrative problem -- 2.1.4. Efron's patch data example -- 2.2. Estimating location and dispersion -- 2.2.1. Means and medians -- 2.2.2. Standard errors and quartiles -- 2.3. Historical notes -- 3. Confidence sets and hypothesis testing -- 3.1. Confidence sets -- 3.1.1. Typical value theorems for M-estimates -- 3.1.2. Percentile method -- 3.1.3. Bias Correction and the Acceleration Constant -- 3.1.4. Iterated Bootstrap -- 3.1.5. Bootstrap Percentile t Confidence Intervals -- 3.2. Relationship Between Confidence Intervals and Tests of Hypotheses -- 3.3. Hypothesis Testing Problems -- 3.3.1. Tendril DX Lead Clinical Trial Analysis --^