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Neither Fixed nor Random: Weighted Least Squares Meta-Analysis

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Author Info

  • T.D. Stanley

    ()

  • Hristos Doucouliagos

    ()

Abstract

We show that a simple weighted least squares meta-regression is statistically superior to either conventional fixed-effects or random-effects meta-analysis. Although weighted least squares has been widely known for many decades among medical researchers, econometricians and particle physicists and its optimal statistical properties have long been established, its implications for meta-analysis have yet to be fully explored or appreciated. Our simulations demonstrate that weighted least squares is preferable to both conventional fixed- and random-effects whether or not there is excess heterogeneity. We show how this simple weighted least squares is an improvement over random-effects in the exact setting for which random-effects meta-analysis is designed.

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File URL: http://www.deakin.edu.au/buslaw/aef/workingpapers/papers/2013_1.pdf
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Bibliographic Info

Paper provided by Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance in its series Economics Series with number 2013_1.

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Date of creation: 23 Feb 2013
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Handle: RePEc:dkn:econwp:eco_2013_1

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Related research

Keywords: meta-analysis; meta-regression; weighted least squares; fixed-effects; random-effects;

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References

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  1. T. D. Stanley, 2008. "Meta-Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(1), pages 103-127, 02.
  2. T.D. Stanley & Stephen B. Jarrell & Hristos Doucouliagos, 2009. "Could It Be Better to Discard 90% of the Data? A Statistical Paradox," Economics Series 2009_13, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  3. Stanley, T D & Jarrell, Stephen B, 1989. " Meta-Regression Analysis: A Quantitative Method of Literature Survey s," Journal of Economic Surveys, Wiley Blackwell, vol. 3(2), pages 161-70.
  4. Hristos Doucouliagos & T.D. Stanley & Margaret Giles, 2011. "Are Estimates of the Value of a Statistical Life Exaggerated?," Economics Series 2011_2, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  5. T.D Stanley & Hristos Doucouliagos, 2007. "Identifying and Correcting Publication Selection Bias in the Efficiency-Wage Literature: Heckman Meta-Regression," Economics Series 2007_11, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  6. Hristos Doucouliagos & T.D. Stanley, 2008. "Theory Competition and Selectivity: Are All Economic Facts Greatly Exaggerated?," Economics Series 2008_06, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
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Cited by:
  1. Lichter, Andreas & Peichl, Andreas & Siegloch, Sebastian, 2014. "The own-wage elasticity of labor demand: A meta-regression analysis," ZEW Discussion Papers 14-016, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.

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