1. Wide Range of Applications: Resampling Methods ; Fields of Application
2. Estimation and the Bootstrap: Precision of an Estimate ; Confidence Intervals ; Improved Confidence Intervals ; Estimating Bias ; Determining Sample Size
3. Software for Use with the Bootstrap and Permutation Tests : AFNI ; Blossom Statistical Analysis Package ; Eviews ; HaploView ; MatLab® ; NCSS ; PAUP ; R ; SAS ; S-Plus ; SPSS Exact Tests ; Stata ; Statistical Calculator ; StatXact ; Testimate
4. Comparing Two Populations: A Distribution-Free Test ; Some Statistical Considerations ; Computing the p-Value ; Other Two-Sample Comparisons ; Two-Sided Test ; Rank Tests ; Matched Pairs ; R Code ; Stata ; Test for Nonequivalence ; Underlying Assumptions ; Comparing Variances
5. Multiple Variables: Single-Valued Test Statistic ; Combining Univariate Tests
6. Experimental Design and Analysis: Separating Signal from Noise ; k-Sample Comparison ; Multiple Factors ; Eliminating the Effects of Multiple Covariates ; Crossover Designs ; Which Sets of Labels Should We Rearrange? ; Determining Sample Size ; Missing Combinations
7. Categorical Data: Fisher's Exact Test. ; Odds Ratio.4 ; Unordered r x c Contingency Tables ; Ordered Statistical Tables ; Multidimensional Arrays
8. Multiple Hypotheses: Controlling the Family-Wise Error Rate ; Controlling the False Discovery Rate ; Software for Performing Multiple Simultaneous Tests ; Testing for Trend
9. Model Building: Regression Models ; Applying the Permutation Test ; Applying the Bootstrap ; Prediction Error ; Validation
10. Classification: Cluster Analysis ; Classification ; Decision Trees ; Decision Trees vs. Regression ; Which Decision Tree Algorithm Is Best for Your Application? ; Reducing the Rate of Misclassification ; Comparison of Classification Tree Algorithms ; Validation vs. Cross-Validation
11. Restricted Permutations: Quasi Independence ; Complete Factorials ; Synchronized Permutations ; Model Validation
Appendix A: Basic Concepts in Statistics: Additive vs. Multiplicative Models ; Central Values ; Combinations and Rearrangements ; Dispersion ; Frequency Distribution and Percentiles ; Linear vs. Nonlinear Regression ; Regression Methods
Appendix B: Proof of Theorems.
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A practitioner's guide to resampling for data analysis, data mining, and modeling by Phillip I. Good. ISBN 9781439855508. Published by CRC in 2012. Publication and catalogue information, links to buy online and reader comments.
