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The Choice of Variables in Observational Studies

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  • D. R. Cox
  • E. J. Snell

Abstract

A review is given of considerations affecting the choice of explanatory variables in observational studies. Aspects of both design and analysis are considered. In particular the choice of explanatory variables in multiple regression is discussed and some recommendations made.

Suggested Citation

  • D. R. Cox & E. J. Snell, 1974. "The Choice of Variables in Observational Studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(1), pages 51-59, March.
    • Handle: RePEc:bla:jorssc:v:23:y:1974:i:1:p:51-59
    DOI: 10.2307/2347053
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    Cited by:

    1. Felix Pretis & Lea Schneider & Jason E. Smerdon & David F. Hendry, 2016. "Detecting Volcanic Eruptions In Temperature Reconstructions By Designed Break-Indicator Saturation," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 403-429, July.
    2. Jesús T. Pastor & JosÉ L. Ruiz & Inmaculada Sirvent, 2002. "A Statistical Test for Nested Radial Dea Models," Operations Research, INFORMS, vol. 50(4), pages 728-735, August.
    3. Heather Battey, 2022. "Heather Battey’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 696-698, July.
    4. Wang, Qin & Yin, Xiangrong, 2008. "A nonlinear multi-dimensional variable selection method for high dimensional data: Sparse MAVE," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4512-4520, May.
    5. Mrs. Swarnali A Hannan, 2015. "If the Fed Acts, How Do You React? The Liftoff Effect on Capital Flows," IMF Working Papers 2015/256, International Monetary Fund.

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