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Generalised interval estimation in the random effects meta regression model

Author

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  • Friedrich, Thomas
  • Knapp, Guido

Abstract

The explanation of heterogeneity when combining different studies is an important issue in meta analysis. Besides including a heterogeneity parameter in the analysis, it is also important to understand the possible causes of heterogeneity. A possibility is to incorporate study-specific covariates in the model that account for between-trial variability. This leads to the random effects meta regression model. Commonly used methods for constructing confidence intervals for the regression coefficients are examined and two new methods based on generalised inference principles are proposed. The different methods are compared by an extensive simulation study with respect to coverage probability and average length.

Suggested Citation

  • Friedrich, Thomas & Knapp, Guido, 2013. "Generalised interval estimation in the random effects meta regression model," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 165-179.
    • Handle: RePEc:eee:csdana:v:64:y:2013:i:c:p:165-179
    DOI: 10.1016/j.csda.2013.03.011
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    References listed on IDEAS

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    1. Viechtbauer, Wolfgang, 2010. "Conducting Meta-Analyses in R with the metafor Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i03).
    2. Hari K. Iyer & C.M. Jack Wang & Thomas Mathew, 2004. "Models and Confidence Intervals for True Values in Interlaboratory Trials," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1060-1071, December.
    3. Jan Hannig & Thomas C. M. Lee, 2009. "Generalized fiducial inference for wavelet regression," Biometrika, Biometrika Trust, vol. 96(4), pages 847-860.
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    Cited by:

    1. Yu, Dalei & Ding, Chang & He, Na & Wang, Ruiwu & Zhou, Xiaohua & Shi, Lei, 2019. "Robust estimation and confidence interval in meta-regression models," Computational Statistics & Data Analysis, Elsevier, vol. 129(C), pages 93-118.
    2. H. Zakerzadeh & A. Jafari, 2015. "Inference on the parameters of two Weibull distributions based on record values," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 25-40, March.
    3. Weber, Frank & Knapp, Guido & Glass, Anne & Kundt, Günther & Ickstadt, Katja, 2020. "Interval estimation of the overall treatment effect in random-effects meta-analyses: Recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods," OSF Preprints 5zbh6, Center for Open Science.

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