The Hartung‐Knapp modification for random‐effects meta‐analysis: A useful refinement but are there any residual concerns?

The modified method for random‐effects meta‐analysis, usually attributed to Hartung and Knapp and also proposed by Sidik and Jonkman, is easy to implement and is becoming advocated for general use. Here, we examine a range of potential concerns about the widespread adoption of this method. Motivated by these issues, a variety of different conventions can be adopted when using the modified method in practice. We describe and investigate the use of a variety of these conventions using a new taxonomy of meta‐analysis datasets. We conclude that the Hartung and Knapp modification may be a suitable replacement for the standard method. Despite this, analysts who advocate the modified method should be ready to defend its use against the possible objections to it that we present. We further recommend that the results from more conventional approaches should be used as sensitivity analyses when using the modified method. It has previously been suggested that a common‐effect analysis should be used for this purpose but we suggest amending this recommendation and argue that a standard random‐effects analysis should be used instead.

[1]  N. Laird,et al.  Meta-analysis in clinical trials. , 1986, Controlled clinical trials.

[2]  Simon G Thompson,et al.  Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews , 2012, International journal of epidemiology.

[3]  Joachim Hartung,et al.  An Alternative Method for Meta‐Analysis , 1999 .

[4]  R R Neutra,et al.  Prevalence of people reporting sensitivities to chemicals in a population-based survey. , 1999, American journal of epidemiology.

[5]  Aditi Sinha,et al.  The authors reply. , 2015, Kidney international.

[6]  G. Casella Conditional inference from confidence sets , 1992 .

[7]  Wolfgang Viechtbauer,et al.  Confidence intervals for the amount of heterogeneity in meta‐analysis , 2007, Statistics in medicine.

[8]  David C Hoaglin,et al.  Misunderstandings about Q and ‘Cochran's Q test' in meta‐analysis , 2016, Statistics in medicine.

[9]  A E Ades,et al.  The Interpretation of Random-Effects Meta-Analysis in Decision Models , 2005, Medical decision making : an international journal of the Society for Medical Decision Making.

[10]  George F Borm,et al.  The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method , 2014, BMC Medical Research Methodology.

[11]  Rebecca M Turner,et al.  Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis , 2011, BMC medical research methodology.

[12]  S Greenland,et al.  Random-effects meta-analyses are not always conservative. , 1999, American journal of epidemiology.

[13]  J. Copas,et al.  A simple confidence interval for meta‐analysis. K. Sidik and J. N. Jonkman, Statistics in Medicine 2002; 21:3153–3159. , 2003, Statistics in medicine.

[14]  Kurex Sidik,et al.  A simple confidence interval for meta‐analysis , 2002, Statistics in medicine.

[15]  Daniel Jackson,et al.  A refined method for multivariate meta-analysis and meta-regression , 2013, Statistics in medicine.

[16]  Wolfgang Viechtbauer,et al.  Conducting Meta-Analyses in R with the metafor Package , 2010 .

[17]  Dan Jackson,et al.  The Significance Level of the Standard Test for a Treatment Effect in Meta-analysis , 2009 .

[18]  Dan Jackson,et al.  Meta‐analysis inside and outside particle physics: two traditions that should converge? , 2013, Research synthesis methods.

[19]  Robert C. Elston,et al.  Authors' reply: AUTHORS' REPLY , 2011 .

[20]  Jack Bowden,et al.  A re-evaluation of the ‘quantile approximation method’ for random effects meta-analysis , 2008, Statistics in medicine.

[21]  J. Hartung,et al.  On tests of the overall treatment effect in meta‐analysis with normally distributed responses , 2001, Statistics in medicine.

[22]  S. Thompson,et al.  Quantifying heterogeneity in a meta‐analysis , 2002, Statistics in medicine.

[23]  Guido Knapp,et al.  Improved tests for a random effects meta‐regression with a single covariate , 2003, Statistics in medicine.

[24]  Ralf Bender,et al.  Methods to estimate the between‐study variance and its uncertainty in meta‐analysis† , 2015, Research synthesis methods.

[25]  Jack Bowden,et al.  Approximate confidence intervals for moment‐based estimators of the between‐study variance in random effects meta‐analysis , 2015, Research synthesis methods.

[26]  Jack Bowden,et al.  How does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts? , 2010 .

[27]  S. Normand,et al.  TUTORIAL IN BIOSTATISTICS META-ANALYSIS : FORMULATING , EVALUATING , COMBINING , AND REPORTING , 1999 .

[28]  Guido Knapp,et al.  Assessing the Amount of Heterogeneity in Random‐Effects Meta‐Analysis , 2006, Biometrical journal. Biometrische Zeitschrift.

[29]  T Stijnen,et al.  Tutorial in biostatistics. Meta-analysis: formulating, evaluating, combining, and reporting by S-L. Normand, Statistics in Medicine, 18, 321-359 (1999) , 2000, Statistics in medicine.

[30]  T. Friede,et al.  Hartung-Knapp-Sidik-Jonkman approach and its modification for random-effects meta-analysis with few studies , 2015, BMC Medical Research Methodology.

[31]  John Mandel,et al.  Consensus Values and Weighting Factors. , 1982, Journal of research of the National Bureau of Standards.

[32]  M. Ghosh,et al.  Current Issues in Statistical Inference: Essays in Honor of D. Basu , 1992 .

[33]  S L Normand,et al.  Meta-analysis: formulating, evaluating, combining, and reporting. , 1999, Statistics in medicine.

[34]  C. Chree,et al.  [Letters to Editor] , 1925, Nature.

[35]  Rose Baker,et al.  Meta‐analysis inside and outside particle physics: convergence using the path of least resistance? , 2013, Research synthesis methods.

[36]  Andrew L. Rukhin Estimating common mean and heterogeneity variance in two study case meta-analysis , 2012 .

[37]  J. Hartung,et al.  A refined method for the meta‐analysis of controlled clinical trials with binary outcome , 2001, Statistics in medicine.

[38]  Gerta Rücker,et al.  Hartung–Knapp method is not always conservative compared with fixed‐effect meta‐analysis , 2016, Statistics in medicine.

[39]  Hisashi Noma,et al.  Confidence intervals for a random‐effects meta‐analysis based on Bartlett‐type corrections , 2011, Statistics in medicine.

[40]  David J Spiegelhalter,et al.  A re-evaluation of random-effects meta-analysis , 2009, Journal of the Royal Statistical Society. Series A,.