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A brief introduction to the methodology of optimal experimental design

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  • Aigner, Dennis J.

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  • Aigner, Dennis J., 1979. "A brief introduction to the methodology of optimal experimental design," Journal of Econometrics, Elsevier, vol. 11(1), pages 7-26, September.
    • Handle: RePEc:eee:econom:v:11:y:1979:i:1:p:7-26
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    Cited by:

    1. Connelly, Luke B., 2003. "Balancing the Number and Size of Sites: An Economic Approach to the Optimal Design of Cluster Samples," MPRA Paper 14676, University Library of Munich, Germany.
    2. Larry L. Orr & Daniel Gubits, 2023. "Some Lessons From 50 Years of Multiarm Public Policy Experiments," Evaluation Review, , vol. 47(1), pages 43-70, February.
    3. Jonathan Chapman & Erik Snowberg & Stephanie Wang & Colin Camerer, 2018. "Loss Attitudes in the U.S. Population: Evidence from Dynamically Optimized Sequential Experimentation (DOSE)," NBER Working Papers 25072, National Bureau of Economic Research, Inc.
    4. Madden, Gary & Bloch, Harry & Hensher, David, 1993. "Australian telephone network subscription and calling demands: evidence from a stated-preference experiment," Information Economics and Policy, Elsevier, vol. 5(3), pages 207-230, October.
    5. Daniel R. Cavagnaro & Richard Gonzalez & Jay I. Myung & Mark A. Pitt, 2013. "Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach," Management Science, INFORMS, vol. 59(2), pages 358-375, February.
    6. Víctor Casero-Alonso & Jesús López-Fidalgo, 2015. "Experimental designs in triangular simultaneous equations models," Statistical Papers, Springer, vol. 56(2), pages 273-290, May.
    7. Aufenanger, Tobias, 2018. "Treatment allocation for linear models," FAU Discussion Papers in Economics 14/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2018.

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