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Cited by 368

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

An Introduction to Bootstrap Methods: Examples and Ideas

STINE, ROBERT·1989·Sociological Methods & Research
DOI 10.1177/0049124189018002003
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Abstract

Bootstrap methods are a collection of sample re-use techniques designed to estimate standard errors and confidence intervals. Making use of numerous samples drawn from the initial observations, these techniques require fewer assumptions and offer greater accuracy and insight than do standard methods in many problems. After presenting the underlying concepts, this introduction focuses on applications in regression analysis. These applications contrast two forms of bootstrap resampling in regression, illustrating their differences in a series of examples that include outliers and heteroscedasticity. Other regression examples use the bootstrap to estimate standard errors of robust estimators in regression and indirect effects in path models. Numerous variations of bootstrap confidence intervals exist, and examples stress the concepts that are common to the various approaches. Suggestions for computing bootstrap estimates appear throughout the discussion, and a section on computing suggests several broad guidelines.

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Metadata

Authors
STINE, R.
Venue
Sociological Methods & Research
Publisher
SAGE Publications
Published
1989-11
Volume
18
Issue
2-3
Pages
243-291
ISSN
  • 0049-1241 (ISSN-L)
  • 1552-8294
DOI
10.1177/0049124189018002003
OpenAlex
W2050059289
Cited by
368
References
4
FWCI
1.38
Type
journal article
Language
en
Open access
closed

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