Hi James,

I used the Revman and CMA meta-analyses Softwares in my meta-analysis researches. 

The first paper was looking at the effectiveness of treatment and the second one was looking at the correlation between two factors. So, in my opinion, I see they are so useful in both cases. 

Regarding this looking at the correlation, I was including the studies using the Odds ratio in measuring the association. However, you can still include some other statistical measures such as the Relative Risk in the same analysis.

I have attached a paper which was helpful in interpreting the magnitudes of ORs. 

I hope my answer was useful...

Thank you Hosam, I will take a look.

Hi James,

Yes, I think that Stata is very useful and user-friendly in conducting a meta-analysis. I have been using it and completed more than 10 studies in meta-analysis. You can also use the "help" command to see how to use "metan". Please find a description of this command below:

Description

These routines provide facilities to conduct meta-analyses of data from more than one study and to graph the results. Either binary (event) or continuous data from two groups may be combined using the metan command. Additionally, intervention effect estimates with corresponding standard errors or confidence intervals may be meta-analysed. Several meta-analytic methods are available, and the results may be displayed graphically in a Forest plot. A test of whether the summary effect measure

is equal to the null is given, as well as a test for heterogeneity, i.e., whether the true effect in all studies is the same. Heterogeneity is also quantified using the I-squared measure (Higgins et al 2003).

metan (the main meta-analysis routine) requires either two, three, four or six variables to be declared. When four variables are specified these correspond to the number of events and non-events in the experimental group followed by those of the control group, and analysis of binary data is performed on the 2x2 table. With six variables, the data are assumed continuous and to be the sample size, mean and standard deviation of the experimental group followed by those of the control group.

If three variables are specified these are assumed to be the effect estimate and its lower and upper confidence interval, and it is suggested that these are log transformed for odds ratios or risk ratios and the eform option used. If two variables are specified these are assumed to be the effect estimate and standard error; again, it is recommended that odds ratios or risk ratios are log transformed.

Thank your for reply, do you have some example syntax that you can share that illustrates the use of the command with correlations as the main effect sizes being evaluated.  Thanking you in advance