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A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling

Publisher: 
Chapman & Hall/CRC
Number of Pages: 
214
Price: 
89.95
ISBN: 
9781439855508
Date Received: 
Thursday, October 20, 2011
Reviewable: 
No
Include In BLL Rating: 
No
Reviewer Email Address: 
Phillip I. Good
Publication Date: 
2011
Format: 
Hardcover
Category: 
Monograph

Wide Range of Applications
The Resampling Methods
Fields of Application

Estimation and the Bootstrap

Precision of an Estimate
Confidence Intervals
Improved Confidence Intervals
Estimating Bias
Determining Sample Size

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

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

Multiple Variables

Single-Valued Test Statistic
Combining Univariate Tests

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

Categorical Data

Fisher’s Exact Test.
Odds Ratio.4
Unordered r × c Contingency Tables
Ordered Statistical Tables
Multidimensional Arrays

Multiple Hypotheses

Controlling the Family-Wise Error Rate
Controlling the False Discovery Rate
Software for Performing Multiple Simultaneous Tests
Testing for Trend

Model Building

Regression Models
Applying the Permutation Test
Applying the Bootstrap
Prediction Error
Validation

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

Restricted Permutations

Quasi Independence
Complete Factorials
Synchronized Permutations
Model Validation

References


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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Saturday, March 10, 2012

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