I have data with very small sample size with 84 participants and very larger sample size with 3,000,000 parcipants in order to pool the prevalence, can I standardize tha data before conducting meta-analysis.
Check these papers:
Haidich A. B. (2010). Meta-analysis in medical research. Hippokratia, 14(Suppl 1), 29–37.
Tawfik, G.M., Dila, K.A.S., Mohamed, M.Y.F. et al. A step by step guide for conducting a systematic review and meta-analysis with simulation data. Trop Med Health 47, 46 (2019). https://doi.org/10.1186/s41182-019-0165-6
the studies will get a weight based on the sample sizes in the meta-analysis calculations.
You could set your inclusion/exclusion criteria to avoid very small sample size studies.
With fixed effect model meta-analysis, small studies with other things being equal, will get very little weight and so the substantive conclusions are unlikely to be affected by including or excluding them.
In random effects model meta-analysis there is substantial heterogeneity then the weights tend to become more equal. In that case even a small study may have almost the same weight as a large one. Some people feel this is undesirable because they believe that (a) small studies are of poorer quality (b) those small studies which they can find are not likely to be a random sample of all the small studies there have ever been.
In your case it therefore (among others) depends on the heterogeneity between the studies.
References:
Article Bias caused by sampling error in meta-analysis with small sample sizes
https://stats.stackexchange.com/questions/92240/why-are-small-sample-sized-avoided-in-meta-analyses
Article The Impact of Study Size on Meta-analyses: Examination of Un...
I hope that helped a little bit. All the best,
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