Meta-analysis is a systematic review of a focused topic in the literature that provides a quantitative estimate for the effect of a treatment intervention or exposure.

Thanks for the reply. I am aware but specifically looking for how to choose quality MA and search engines..would you be able to advise on that?TIA

Very interesting.

Good morning

I recommended to find articles in Scopus

Best regards

Ph,D Ingrid del Valle García Carreño

Dear Nilakshika Ranasinghe,

some days ago, I also started a discussion/posted a similar question on RG regarding drafting literatur reviews.

https://www.researchgate.net/post/What_are_your_Tips_Tricks_for_drafting_Literature_Reviews

Maybe some of the answers there will provide you with further insights. Especially, the link given by Nasser Abdo Saif Almuraqab I found quite ressourceful.

Best regards

Ralf

Check out COCHRANE for Meta-analysis.

Meta-analysis refers to the statistical analysis of the data from independent primary studies focused on the same question, which aims to generate a quantitative estimate of the studied phenomenon, for example, the effectiveness of the intervention (Gopalakrishnan and Ganeshkumar, 2013).

Steps in Quantitative Literature Review

All meta-analytic efforts prescribe to a similar workflow, outlined as follows:

1) Formulate research question

• Define primary and secondary objectives

• Determine breadth of question

2) Identify relevant literature

• Construct search strategy: rapid or systematic search

• Screen studies and determine eligibility

3) Extract and consolidate study-level data

• Extract data from relevant studies

• Collect relevant study-level characteristics and experi-mental covariates

• Evaluate quality of studies

• Estimate model parameters for complex relation-ships (optional)

4) Data appraisal and preparation

• Compute appropriate outcome measure

• Evaluate extent of between-study inconsistency (heterogeneity)

• Perform relevant data transformations

• Select meta-analytic model

5) Synthesize study-level data into summary measure

• Pool data and calculate summary measure and confidence interval

6) Exploratory analyses

• Explore potential sources of heterogeneity (ex. biological or experimental)

• Subgroup and meta-regression analyses

7) Knowledge synthesis

• Interpret findings

• Provide recommendations for future work