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An Introduction to Bootstrap Methods

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  • ROBERT STINE

    (University of Pennsylvania)

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.

Suggested Citation

  • Robert Stine, 1989. "An Introduction to Bootstrap Methods," Sociological Methods & Research, , vol. 18(2-3), pages 243-291, November.
  • Handle: RePEc:sae:somere:v:18:y:1989:i:2-3:p:243-291
    DOI: 10.1177/0049124189018002003
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    Cited by:

    1. M.L. Nores & M.P. Díaz, 2016. "Bootstrap hypothesis testing in generalized additive models for comparing curves of treatments in longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 810-826, April.
    2. Andreea N. Kiss & Pamela S. Barr, 2015. "New venture strategic adaptation: The interplay of belief structures and industry context," Strategic Management Journal, Wiley Blackwell, vol. 36(8), pages 1245-1263, August.
    3. Wiklund, Johan & Yu, Wei & Tucker, Reginald & Marino, Louis D., 2017. "ADHD, impulsivity and entrepreneurship," Journal of Business Venturing, Elsevier, vol. 32(6), pages 627-656.
    4. Ventura Charlin & Arturo Cifuentes, 2017. "On the correlation between stocks and art market returns," Applied Economics Letters, Taylor & Francis Journals, vol. 24(2), pages 128-131, January.
    5. Holthausen, Robert W. & Larcker, David F. & Sloan, Richard G., 1995. "Business unit innovation and the structure of executive compensation," Journal of Accounting and Economics, Elsevier, vol. 19(2-3), pages 279-313, April.
    6. Shteynberg, Garriy & Leslie, Lisa M. & Knight, Andrew P. & Mayer, David M., 2011. "But Affirmative Action hurts Us! Race-related beliefs shape perceptions of White disadvantage and policy unfairness," Organizational Behavior and Human Decision Processes, Elsevier, vol. 115(1), pages 1-12, May.
    7. Winker, Peter, 1991. "Zur Messung der Lohndifferenzierung mit Entropiemaßen," Discussion Papers, Series II 158, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    8. Ashleigh Shelby Rosette & Andrew M. Carton & Lynn Bowes-Sperry & Patricia Faison Hewlin, 2013. "Why Do Racial Slurs Remain Prevalent in the Workplace? Integrating Theory on Intergroup Behavior," Organization Science, INFORMS, vol. 24(5), pages 1402-1421, October.
    9. Janfry Sihite & Sofjan Assauri & Rizal Edy Halim, 2018. "Brand Promise and Reputation Against the Campaign of a Political Party," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 227-240.
    10. Hochwarter, Wayne A. & Ferris, Gerald R. & Gavin, Mark B. & Perrewe, Pamela L. & Hall, Angela T. & Frink, Dwight D., 2007. "Political skill as neutralizer of felt accountability--job tension effects on job performance ratings: A longitudinal investigation," Organizational Behavior and Human Decision Processes, Elsevier, vol. 102(2), pages 226-239, March.

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