Bootstrapping

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Christopher Z. Mooney - University of Illinois at Chicago, USA
Robert D. Duval - West Virginia University, USA

Volume: 95

Series:
Quantitative Applications in the Social Sciences

August 1993 | 80 pages | SAGE Publications, Inc

Description
Contents

"This book is. . . clear and well-written. . . anyone with any interest in the basis of quantitative analysis simply must read this book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Using real data examples, this volume shows how to apply bootstrapping when the underlying sampling distribution of a statistic cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, it discusses the advantages and limitations of four bootstrap confidence interval methods--normal approximation, percentile, bias-corrected percentile, and percentile-t. The book concludes with a convenient summary of how to apply this computer-intensive methodology using various available software packages.

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ISBN: 9780803953819	Paperback	Suggested Retail Price: $46.00	Bookstore Price: $36.80
ISBN: 9781452210506	Electronic Version	Suggested Retail Price: $38.00	Bookstore Price: $30.40

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PART ONE: INTRODUCTION

Traditional Parametric Statistical Inference

Bootstrap Statistical Inference

Bootstrapping a Regression Model

Theoretical Justification

The Jackknife

Monte Carlo Evaluation of the Bootstrap

PART TWO: STATISTICAL INFERENCE USING THE BOOTSTRAP

Bias Estimation

Bootstrap Confidence Intervals

PART THREE: APPLICATIONS OF BOOTSTRAP CONFIDENCE INTERVALS

Confidence Intervals for Statistics With Unknown Sampling Distributions

Inference When Traditional Distributional Assumptions Are Violated

PART FOUR: CONCLUSION

Future Work

Limitations of the Bootstrap

Concluding Remarks

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