While Egger's Test is a valuable tool, it has limitations. Firstly, it assumes that the true effect sizes are normally distributed, which may not always be the case. Secondly, the test can be overly sensitive, identifying asymmetry due to reasons other than publication bias, such as heterogeneity in study designs or populations. Lastly, Egger's Test requires a reasonably large sample of studies to be effective, limiting its utility in smaller meta-analyses.
