+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Multivariate meta-analysis for non-linear and other multi-parameter associations


      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd.

          Related collections

          Most cited references60

          • Record: found
          • Abstract: not found
          • Book: not found

          R: a language and environment for statistical computing

            • Record: found
            • Abstract: found
            • Article: not found

            Regression Modeling Strategies

            Springer Series in Statistics
              • Record: found
              • Abstract: found
              • Article: not found

              Small sample inference for fixed effects from restricted maximum likelihood.

              Restricted maximum likelihood (REML) is now well established as a method for estimating the parameters of the general Gaussian linear model with a structured covariance matrix, in particular for mixed linear models. Conventionally, estimates of precision and inference for fixed effects are based on their asymptotic distribution, which is known to be inadequate for some small-sample problems. In this paper, we present a scaled Wald statistic, together with an F approximation to its sampling distribution, that is shown to perform well in a range of small sample settings. The statistic uses an adjusted estimator of the covariance matrix that has reduced small sample bias. This approach has the advantage that it reproduces both the statistics and F distributions in those settings where the latter is exact, namely for Hotelling T2 type statistics and for analysis of variance F-ratios. The performance of the modified statistics is assessed through simulation studies of four different REML analyses and the methods are illustrated using three examples.

                Author and article information

                Stat Med
                Stat Med
                Statistics in Medicine
                Blackwell Publishing Ltd
                20 December 2012
                16 July 2012
                : 31
                : 29
                : 3821-3839
                [a ]Department of Medical Statistics, London School of Hygiene and Tropical Medicine London, U.K.
                [b ]Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine London, U.K.
                Author notes
                *Correspondence to: Antonio Gasparrini, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, U.K.
                Copyright © 2012 John Wiley & Sons, Ltd.

                Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

                : 09 August 2011
                : 11 May 2012
                Research Articles

                meta-analysis,multivariate analysis,multivariate meta-analysis,non-linear,splines
                meta-analysis, multivariate analysis, multivariate meta-analysis, non-linear, splines


                Comment on this article