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Power analysis and sample sizes: A Binding frontier approach

Author

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  • Subrato Banerjee

    (Indian Statistical Institute, Delhi
    Institute of Economic Growth)

Abstract

I introduce a completely new (non-parametric) approach to determine (satislcing) sample sizes, when dynamic sampling and stopping rules are not feasible, and when no assumption can be made on the underlying (and unknown) distribution(s) that is (are) believed to generate observed experimental data. The method proposed, that relies on the construction of a 'binding function', is shown to be a general solution for a class of problems associated with decision functions that frequently interest (lab and leld) experimental researchers in the areas of economics and psychology.

Suggested Citation

  • Subrato Banerjee, 2015. "Power analysis and sample sizes: A Binding frontier approach," Discussion Papers 15-04, Indian Statistical Institute, Delhi.
    • Handle: RePEc:alo:isipdp:15-04
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    References listed on IDEAS

    as
    1. 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.
    2. Stephen E. Chick & Peter Frazier, 2012. "Sequential Sampling with Economics of Selection Procedures," Management Science, INFORMS, vol. 58(3), pages 550-569, March.
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    Cited by:

    1. Subrato Banerjee & Basri Savitha, 2021. "Competition reduces profitability: the case of the Indian life microinsurance industry," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(3), pages 383-398, July.
    2. Subrato Banerjee & Benno Torgler, 2020. "A Non-Bayesian Approach to Scientific Inference on Treatment-Effects," CREMA Working Paper Series 2020-14, Center for Research in Economics, Management and the Arts (CREMA).

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    More about this item

    Keywords

    Sampling theory; Hypothesis testing; Power analysis;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

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