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Power by simulation

Author

Listed:
  • A. H. Feiveson

    (NASA Johnson Space Center)

Abstract

This paper describes how to write Stata programs to estimate the power of virtually any statistical test that Stata can perform. Examples given include the t test, Poisson regression, Cox regression, and the nonparametric rank-sum test. Copyright 2002 by Stata Corporation.

Suggested Citation

  • A. H. Feiveson, 2002. "Power by simulation," Stata Journal, StataCorp LP, vol. 2(2), pages 107-124, May.
    • Handle: RePEc:tsj:stataj:v:2:y:2002:i:2:p:107-124
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    Citations

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    Cited by:

    1. Richard Hooper, 2013. "Versatile sample-size calculation using simulation," Stata Journal, StataCorp LP, vol. 13(1), pages 21-38, March.
    2. Theresa Wimberley & Erik Parner & Henrik Støvring, 2013. "Stata as a numerical tool for scientific thought experiments: A tutorial with worked examples," Stata Journal, StataCorp LP, vol. 13(1), pages 3-20, March.
    3. Eszter Czibor & David Jimenez‐Gomez & John A. List, 2019. "The Dozen Things Experimental Economists Should Do (More of)," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 371-432, October.
    4. Brendon McConnell & Marcos Vera-Hernandez, 2015. "Going beyond simple sample size calculations: a practitioner's guide," IFS Working Papers W15/17, Institute for Fiscal Studies.
    5. Leah H. Palm-Forster & Paul J. Ferraro & Nicholas Janusch & Christian A. Vossler & Kent D. Messer, 2019. "Behavioral and Experimental Agri-Environmental Research: Methodological Challenges, Literature Gaps, and Recommendations," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(3), pages 719-742, July.
    6. Bellemare, Charles & Bissonnette, Luc & Kröger, Sabine, 2014. "Statistical Power of Within and Between-Subjects Designs in Economic Experiments," IZA Discussion Papers 8583, Institute of Labor Economics (IZA).
    7. Timothy R. Wojan & Jason P. Brown & Dayton M. Lambert, 2014. "What to Do about the "Cult of Statistical Significance"? A Renewable Fuel Application using the Neyman-Pearson Protocol," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 36(4), pages 674-695.
    8. Brian Albert Monroe, 2020. "The statistical power of individual-level risk preference estimation," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 6(2), pages 168-188, December.

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