Hi all,
I have performed a meta-analysis and found a certain pooled effect with 95% CI that was not statistically significant (p>0.05). Consequently, I have done a sensitivity analysis for which I have excluded studies that contributed most to heterogeneity.
In order to do so I used the Leave-one-out method to determine which studies contributed most and have excluded studies so heterogeneity (I^2) would decrease to 35% or less.
However, the pooled effect remained nearly the same but the 95% CI became narrower and my result is now statistically significant (p<0.05).
I think this is because heterogeneity is linked to the standard error of each study, and when excluding studies with large standard errors the overall 95% CI becomes narrower to the point where zero is no longer included in the confidence interval making the result statistically significant.
Is my rationale correct?
Thanks in advance,
Tom
I have performed a meta-analysis and found a certain pooled effect with 95% CI that was not statistically significant (p>0.05). Consequently, I have done a sensitivity analysis for which I have excluded studies that contributed most to heterogeneity.
In order to do so I used the Leave-one-out method to determine which studies contributed most and have excluded studies so heterogeneity (I^2) would decrease to 35% or less.
However, the pooled effect remained nearly the same but the 95% CI became narrower and my result is now statistically significant (p<0.05).
I think this is because heterogeneity is linked to the standard error of each study, and when excluding studies with large standard errors the overall 95% CI becomes narrower to the point where zero is no longer included in the confidence interval making the result statistically significant.
Is my rationale correct?
Thanks in advance,
Tom