■ Meta Analysis basics (Source: Self made notes: Lectures from ANU, Australia)
Generally, Meta Analysis is a statistical procedure to combine data from the multiple studies and thus study them.
In actual sense, to conduct a meta analysis it requires a huge costs and knowledge as well that are to be dealt in complex issues such as increasing precision and providing external validity.
● So why Meta Analysis then ?
♢ Sometimes research might be biased.
♢ The studies are often underpowered.
♢ The studies might be partaially informative about each other.
● How to do it ?
- Select topic
- Searching
- Screening
- Data Extraction
- Analysis
Let's see its sample process diagram
♢ 1st we see the search resources
♢ Then we search the String developmen.
♢ Then either one of two are chosen: Scripted Scraping Searches and Manual Searches.
♢ Then Duplicate Screening
♢ Again for the Screening Criteria Development the Title Screening are chosen as Double Entry and then followed by Reconciliation.
♢ The reference checking is done
♢ Again duplicate screening
♢ Search results
♢ Again Double Entry and Reconciliation
♢ Finding full text of papers
♢ Then the screened papers.
After these, the process goes out to the data analysis.
● Analysis
The analysis of Fixed Effect: There is one true fixed effects.
Random Effect: True effects may vary by the study.
Mixed Model: True effects may vary by the study, and we can explain some of that.
In STATA the 'metan' package is used wheras in R 'meta' package must be downloaded ( discuss about R and STATA later in upcoming blogs).
We'll see the Heterogeneity of model and Estimating Biases (Funnel Plots, Caliper Tests) in the upcoming parts.
To be contd...
Aditya Pokhrel
MBA, MA Economics, MPA
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