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metandi: Meta-analysis of diagnostic accuracy using hierarchical logistic regression

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  • Roger M. Harbord

    () (University of Bristol)

  • Penny Whiting

    (University of Bristol)

Abstract

Meta-analysis of diagnostic test accuracy presents many challenges. Even in the simplest case, when the data are summarized by a 2 × 2 table from each study, a statistically rigorous analysis requires hierarchical (multilevel) models that respect the binomial data structure, such as hierarchical logistic regression. We present a Stata package, metandi, to facilitate the fitting of such models in Stata. The commands display the results in two alternative parameterizations and produce a customizable plot. metandi requires either Stata 10 or above (which has the new command xtmelogit), or Stata 8.2 or above with gllamm installed. Copyright 2009 by StataCorp LP.

Suggested Citation

  • Roger M. Harbord & Penny Whiting, 2009. "metandi: Meta-analysis of diagnostic accuracy using hierarchical logistic regression," Stata Journal, StataCorp LP, vol. 9(2), pages 211-229, June.
  • Handle: RePEc:tsj:stataj:v:9:y:2009:i:2:p:211-229
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    References listed on IDEAS

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    1. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "GLLAMM Manual," U.C. Berkeley Division of Biostatistics Working Paper Series 1160, Berkeley Electronic Press.
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    Cited by:

    1. Ian R. White, 2011. "Multivariate random-effects meta-regression: Updates to mvmeta," Stata Journal, StataCorp LP, vol. 11(2), pages 255-270, June.

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