The term 'meta-analysis' refers to combining the quantitative results of multiple studies to achieve a summary statistic. It does not refer to one type of statistical technique in particular.

If you have mean and confidence interval you can do the most common form of meta-analysis the inverse-variance method. You may need to convert the confidence intervals into standard deviations beforehand, depending on your software. There are numerous other meta-analysis methods, but without knowing the details of your particular studies, one cannot say which would be appropriate for you.

If you think the studies are too different to combine in terms of design, then you can do a narrative synthesis of the results, and list the findings of the studies in a table.

Further reading: https://training.cochrane.org/handbook/current/chapter-10

This model can help you estimate the overall effect of the intervention and incorporate the between-study heterogeneity. By employing MCMC techniques, you can obtain posterior distributions for the parameters of interest, such as effect sizes or treatment effects.

Using MCMC, you can quantify the effect of the intervention while considering the variation across studies, providing a more comprehensive analysis than a traditional meta-analysis. However, implementing MCMC requires a solid understanding of Bayesian statistics and programming skills to conduct the analysis.

Dear Joseph Whittaker and Usman Ghani ,

I'm very grateful for your responses! Thank you so much for the in-sights and recommendation. I'll try them out and see if they work for my study. Thanks again! May God bless both of you.

You're welcome! I'm glad I could help. If you have any more questions in the future, feel free to ask. Best of luck with your study, and may God bless you too!

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