metandi: Meta–analysis of diagnostic accuracy using hierarchical logistic regression
Roger M. Harbord
Department of Social Medicine
University of Bristol
Bristol, UK
roger.harbord@bristol.ac.uk
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Penny Whiting
Department of Social Medicine
University of Bristol
Bristol, UK
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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.
View all articles by these authors:
Roger M. Harbord, Penny Whiting
View all articles with these keywords:
metandi, metandiplot, diagnosis, meta-analysis, sensitivity and specificity, hierarchical models, generalized mixed models, gllamm, xtmelogit, receiver operating characteristic (ROC), summary ROC, hierarchical summary ROC
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