What does a p-value of less than .05 indicate in a meta-analysis?

A p-value of less than .05 is a commonly accepted threshold in statistical analysis that indicates statistical significance. In the context of a meta-analysis, this means that the results are unlikely to be due to random chance, suggesting that there is a statistically significant effect or association present in the studies being analyzed. This threshold helps researchers determine whether their findings can be considered robust and reliable, leading to further implications for practice, policy, or further research.

In a meta-analysis, achieving a p-value below this threshold typically supports the hypothesis that the intervention or effect being studied has a meaningful impact. It reinforces the notion that the combined evidence from multiple studies is sufficient to draw conclusions about the effect in question, thereby enhancing the confidence in the results.

The remaining options center around different concepts. Risk of bias pertains to the quality and reliability of individual studies within the meta-analysis rather than the significance of the results themselves. Data validity issues refer to concerns regarding the accuracy and trustworthiness of the data used in the analysis, which is distinct from statistical significance. The mention of a fixed effects model relates to the modeling approach used in the analysis rather than the interpretation of the p-value itself. Therefore, the interpretation of a p-value underlines the importance of statistical significance, confirming findings