Comprehensive meta analysis outliers
A study is considered as an outlier if its standardized residual is greater than 3 in absolute magnitude.Ī numeric vector specifying the observed effect sizes in the collected studies they are assumed to be normally distributed.Ī numeric vector specifying the within-study variances.Ī character string specified as either "FE" or "RE". A common method to detect outliers directly is to define a study as an outlier if the studys confidence interval does not overlap with the confidence interval. I would like to display the studies sorted according to their ES and report both Mean ESs in the forest plot. Accordingly, I calculate a mean ES with ( k 10) and without the outlier ( k 9). Outlier analyses showed that Study 3 is an outlier leading to an overestimation of the mean weighted ES. They provide a list of about 100 discordancy tests for detecting outliers in data following well known distributions. A comprehensive treatment of outliers appears in Barnet and Lewis (1994). Missing studies suppressed by publication bias in a meta-analysis usually lead to. studies that consider outlier identification as their primary objective are in the field of statistics. A forest plot of the meta-analysis with outliers removed can be generated directly by plugging the output of the function into the forest function.
#Comprehensive meta analysis outliers how to
While researchers generally agree that it is necessary to examine outlier and influential case diagnostics when conducting a meta-analysis, limited studies have addressed how to obtain such diagnostic measures in the context of a meta-analysis. Outliers and the pre-specified direction of missing studies could have. When outliers are found, the function automatically recalculates the meta-analysis results, using the same settings as in the object provided in x, but excluding the detected outliers. Calculates the standardized residual for each study in meta-analysis using the methods desribed in Chapter 12 in Hedges and Olkin (1985) and Viechtbauer and Cheung (2010). Assume there are 10 studies in the meta-analysis. The presence of outliers and influential cases may affect the validity and robustness of the conclusions from a meta-analysis.