Note that the estimated overall odds ratio (and corresponding CI) is slightly different than the one obtained earlier. The following forest plot is also generated: I-squared (variation in OR attributable to heterogeneity) = 2.5% The same analysis run in Stata using the metan command (with default settings) yields the following results: 39$), although Tarone's test is suggestive of potential heterogeneity. The Q-test for heterogeneity is not significant ($Q(16) = 16.86, p =. The overall effect is clearly statistically significant (with both the Wald-type z-test and the Cochran-Mantel-Haenszel chi-square test in close agreement). 299) \times 100%$) in patients receiving an anti-infective-treated catheter instead of a standard catheter. In other words, the odds of an infection are estimated to be approximately 70% lower (i.e., $(1. Therefore, the odds ratio is estimated to be. H^2 (total variability / sampling variability): 1.05Ĭochran-Mantel-Haenszel Test: CMH = 32.214, df = 1, p-val < 0.001 I^2 (total heterogeneity / total variability): 5.12% Res1 <- rma.mh (measure = "OR", ai =ai, n1i =n1i, ci =ci, n2i =n2i, data =dat ) print (res1, digits = 3 ) Equal-Effects Model (k = 18) Also, no cases (infections) were observed in either group in the Yucel (2004) study.Īn analysis of these data using the Mantel-Haenszel method can be carried out with:
Note that the number of infections was quite low in many studies, with zero cases observed in several of the treatment groups. Variables ai and ci indicate the number of CRBSIs in patients receiving an anti-infective or a standard catheter, respectively, while n1i and n2i indicate the total number of patients in the respective groups. The data to be used for this example are stored in the dataset dat.nielweise2007: The reason for such discrepancies is explained further below using an illustrative dataset from a meta-analysis comparing the risk of catheter-related bloodstream infection (CRBSI) when using anti-infective-treated versus standard catheters in the acute care setting (Niel-Weise et al., 2007). By default, the results obtained may differ slightly from those obtained via the metan function in Stata (for more details, see Harris et al., 2008 Sterne, 2009), the Review Manager (RevMan) from the Cochrane Collaboration, or Comprehensive Meta-Analysis (CMA). The method is available in the metafor package via the rma.mh() function. The method is particularly advantageous when aggregating a large number of studies with small sample sizes (the so-called sparse data or increasing strata case). The Mantel-Haenszel method is an approach for fitting meta-analytic equal-effects models when dealing with studies providing data in the form of 2x2 tables or in the form of event counts (i.e., person-time data) for two groups (Mantel & Haenszel, 1959).