Simple heterogeneity variance estimation for meta‐analysis

By Kurex Sidik, Jeffrey N. Jonkman. 2005

259 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/95ef894f644d4c51f6ae1d5e9b4feb04392f0482

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

Confidence intervals for the amount of heterogeneity in meta‐analysis (2007, methodology): “As discussed earlier, the lower and upper bounds of the con dence interval obtained with the method proposed by Sidik and Jonkman [15] are always greater than zero.”
A comparison of heterogeneity variance estimators in simulated random‐effects meta‐analyses (2018, background): “The review identified 12 relevant simulation studies, but there was little consensus across the various authors' recommendations.(2-4,8,12-19) This may have been caused by a potential conflict of interest among the authors of all but four of these studies(3,12,13,17); the authors of these eight stud”
Methods to estimate the between‐study variance and its uncertainty in meta‐analysis† (2015, methodology): “…estimate is acceptable when true levels of the between-study variance are small or close to zero and k is large, whereas when τ2 is large, the DL estimator can produce estimates with significant negative bias (Bowden et al., 2011; Novianti et al., 2014; Sidik and Jonkman, 2007, 2005a, 2005b).”
The Synthesis of Regression Slopes in Meta-Analysis. (2007, background): “A variety of estimators for the between-studies variance exist (e.g., Hedges and Olkin (1985); Sidik and Jonkman, 2005) and an estimated between-studies variance could then be added to each study’s sampling variance to augment its uncertainty.”
The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method (2014, methodology): “Simulations have shown that the HKSJ method performs better than DL, especially when there is heterogeneity and the number of studies in the meta-analysis is small [4-14].”
Conducting Meta-Analyses in R with the metafor Package (2010, methodology): “…(Hedges and Olkin 1985; Rau-denbush 2009), the DerSimonian-Laird estimator (DerSimonian and Laird 1986; Raudenbush 2009), the Sidik-Jonkman estimator (Sidik and Jonkman 2005a,b), the maximum-likelihood or restricted maximum-likelihood estimator (Viechtbauer 2005; Raudenbush 2009), or the empirical…”