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Going beyond simple sample size calculations: a practitioner's guide

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  • Brendon McConnell
  • Marcos Vera‐Hernández

Abstract

Basic methods to compute required sample sizes are well understood and supported by widely available software. However, researchers often oversimplify their sample size calculations, overlooking relevant features of their experimental design. This paper compiles and systematises existing methods for sample size calculations for continuous and binary outcomes, both with and without covariates, and for both clustered and non‐clustered randomised controlled trials. We present formulae accommodating panel data structures and uneven designs, and provide guidance on optimally allocating sample size between the number of clusters and the number of units per cluster. In addition, we discuss how to adjust calculations for multiple hypothesis testing and how to estimate power in more complex designs using simulation methods.

Suggested Citation

  • Brendon McConnell & Marcos Vera‐Hernández, 2025. "Going beyond simple sample size calculations: a practitioner's guide," Fiscal Studies, John Wiley & Sons, vol. 46(3), pages 323-348, September.
  • Handle: RePEc:wly:fistud:v:46:y:2025:i:3:p:323-348
    DOI: 10.1111/1475-5890.70005
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    References listed on IDEAS

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    1. Anderson, Michael L., 2008. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1481-1495.
    2. Kenneth F Schulz & Douglas G Altman & David Moher & for the CONSORT Group, 2010. "CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomised Trials," PLOS Medicine, Public Library of Science, vol. 7(3), pages 1-7, March.
    3. repec:mpr:mprres:7874 is not listed on IDEAS
    4. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    5. Richard Hooper, 2013. "Versatile sample-size calculation using simulation," Stata Journal, StataCorp LLC, vol. 13(1), pages 21-38, March.
    6. repec:feb:artefa:0087 is not listed on IDEAS
    7. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    8. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
    9. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    10. David McKenzie, 2025. "Designing and analysing powerful experiments: practical tips for applied researchers," Fiscal Studies, John Wiley & Sons, vol. 46(3), pages 305-322, September.
    11. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
    12. McKenzie, David, 2012. "Beyond baseline and follow-up: The case for more T in experiments," Journal of Development Economics, Elsevier, vol. 99(2), pages 210-221.
    13. Levitt, Steven D. & List, John A., 2009. "Field experiments in economics: The past, the present, and the future," European Economic Review, Elsevier, vol. 53(1), pages 1-18, January.
    14. Jerry A. Hausman & David A. Wise, 1985. "Introduction to "Social Experimentation"," NBER Chapters, in: Social Experimentation, pages 1-10, National Bureau of Economic Research, Inc.
    15. Hausman, Jerry A. & Wise, David A. (ed.), 1985. "Social Experimentation," National Bureau of Economic Research Books, University of Chicago Press, number 9780226319407, March.
    16. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    17. repec:mpr:mprres:6371 is not listed on IDEAS
    18. Jerry A. Hausman & David A. Wise, 1985. "Social Experimentation," NBER Books, National Bureau of Economic Research, Inc, number haus85-1.
    19. John List & Sally Sadoff & Mathis Wagner, 2011. "So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design," Experimental Economics, Springer;Economic Science Association, vol. 14(4), pages 439-457, November.
    20. Kontopantelis, Evangelos & Springate, David A & Parisi, Rosa & Reeves, David, 2016. "Simulation-Based Power Calculations for Mixed Effects Modeling: ipdpower in Stata," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i12).
    21. Gary Burtless, 1995. "The Case for Randomized Field Trials in Economic and Policy Research," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 63-84, Spring.
    22. Manoj Mohanan & Katherine Donato & Grant Miller & Yulya Truskinovsky & Marcos Vera-Hernández, 2021. "Different Strokes for Different Folks? Experimental Evidence on the Effectiveness of Input and Output Incentive Contracts for Health Care Providers with Varying Skills," American Economic Journal: Applied Economics, American Economic Association, vol. 13(4), pages 34-69, October.
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    1. David McKenzie, 2025. "Designing and analysing powerful experiments: practical tips for applied researchers," Fiscal Studies, John Wiley & Sons, vol. 46(3), pages 305-322, September.

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