Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

BMC Medical Research Methodology

Wolfgang Viechtbauer¹  Kirsty Rhodes²  Rebecca Turner²  Dan Jackson² 

[1] Department of Psychiatry and Psychology School for Mental Health and Neuroscience Faculty of Health, Medicine, and Life Sciences Maastricht University, P.O. Box 616 (VIJV1), 6200 MD, Maastricht, The Netherlands;MRC Biostatistics Unit, Cambridge, UK

关键词: Quadratic forms;    Meta-regression;    Informative priors;    Heterogeneity;   

Others  :  1091101
DOI  :  10.1186/1471-2288-14-103

 received in 2014-04-25, accepted in 2014-08-28,  发布年份 2014

【 摘 要 】

Background

Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented.

Methods

Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions.

Results

Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples.

Conclusions

Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose.

【 授权许可】

   
2014 Jackson et al.; licensee BioMed Central Ltd.

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