Meta-Analysis – Definition, Purpose, And How To Conduct It

To conduct a quality meta-analysis, you need to identify an area in which the effect of treatment is uncertain. It is also recommended that you collect as many studies similar to the effect as possible, so that you can compare them and gain a better understanding of it.

 This helps the researcher understand the magnitude of the effect and how it compares to other studies.

Purpose Of Meta-Analysis 

The purpose of meta-analysis extends beyond simply combining results from studies to provide a statistical assessment. It also helps to point out:

• Any potential reasons for variations and differences in results are also known as heterogeneity in meta-analysis. Some popular reasons for this might be differences in sample size or variations in research analysis methods.
• The reported estimate of the effect size in the literature is greater than that of any individual study. Combining multiple studies reduces research bias and the chances of random errors.

How To Conduct A Meta-Analysis

Before conducting a meta-analysis and defining the research scope, it is necessary to evaluate the number of publications that have grown over the years.

It can be challenging to scan and skim through a large number of studies and literature reviews, which is why it is essential to define the research question with care, including only relevant aspects.

Here are the steps on how to perform a meta-analysis:

Step 1: Formulate a Research Question

Formulate a research question that showcases the effects or interventions to be studied. This is primarily a binary question, such as “Does drug X improve outcome Y” in clinical studies.

Step 2: Conduct a Systematic Review

Conduct a systematic review that analyses and synthesises all data related to the one research question.

Step 3: Gather Data

Gather all relevant data, including sample sizes and research methods used, to indicate data variability. All decide which dependent variables are allowed.

Step 4: Selection of Criteria

The selection of criteria is also a crucial step, as it is necessary to determine whether published or unpublished studies should be included. Based on the research question, it is essential to select studies that are of high quality and relevant.

Step 5: Choose Meta-Analytic Methods and Software

Choosing the proper meta-analytic methods and meta-analysis software for use in a meta-analysis is another significant step. Some techniques used are traditional univariate meta-analysis, meta-regression, and meta-analytic structural equation modeling methods.

Step 6: Evaluate Data with a Forest Plot

When evaluating the data, it is necessary to use a meta-analysis forest plot, which is a graphical representation of the results from a meta-analysis study. Its visual representation helps to understand the heterogeneity among studies and facilitates comparison of the overall effect sizes of an intervention.

Step 7: Report the Results

The final step of literature meta-analysis is to report the results. They should be comprehensive and precise for the reader’s understanding.

Meta-Analysis Uses

Meta-analyses are used in both types of research, applied and basic research.

• Pharmaceutical companies use meta-analyses to gain approval for new drugs, such as antibiotics for bacterial infections. Even regulatory authorities utilize this research method to obtain approval for various processes. Hence, meta-analysis is used in medicine, crime, education, and psychology for applied research.
• In terms of basic research, it is applied in various fields, including sociology, finance, economics, marketing, and social psychology. 

Strengths of Meta-Analysis

There are many key benefits of meta-analysis in research studies, as it is a powerful tool. Here are some strengths of it:

• A meta-analysis typically follows a systematic review, ensuring the end product is reliable and accurate.
• It has great statistical power, as it combines multiple studies rather than relying on a single study, which might suffer from insufficient data.
• This analysis can either confirm or refute existing research. Either way, it gives a confirmatory data analysis.
• It is regarded highly in the scientific community, as it provides an objective and solid analysis of evidence.

Challenges Associated With Meta-Analysis

Meta-analysis also presents specific challenges that result in limitations when employing this statistical quantitative approach. Some challenges faced by meta-analyses are:

• It is not always possible to predict the outcome of a large-scale study. This is because meta-analysis primarily relies on small-scale studies, which do not accurately represent the broader population.
• A decent meta-analysis cannot make up for flawed or poor research designs. Thus, it can not control the potential for bias to arise in studies. Therefore, it is recommended to include only research with sound methodologies, known as “best evidence synthesis.”

Meta-Analysis Vs Systematic Review

A systematic review is a comprehensive analysis of existing research, whereas a meta-analysis is a statistical analysis or a combination of results from two or more separate studies.