The Role of Meta-Analysis in Scientific Studies

A meta-analysis is a type of statistical analysis in which the results of multiple studies are combined and then analyzed. Researchers can perform this type of study when there have been a number of previous studies looking at the same question.

A meta-analysis is essentially a study of past studies. It is used to get an integrated result. A researcher reviews previously published studies on a topic, then analyzes the various results to find general trends across the studies. It can be used in psychology, general medical practice, or other fields.

This article discusses why a meta-analysis might be used and why this type of research is important. It also covers some of the potential advantages and disadvantages of performing a meta-analysis in psychology research.

Why Is Meta-Analysis Important?

With new studies from around the world constantly being published, the amount of research is overwhelming. This is true even for the most experienced practitioner.

A meta-analysis is helpful because it's designed to summarize information. It follows a few general principles. A meta-analysis:

• Is done systematically
• Follows certain criteria
• Contains a pool of results
• Is based on a quantitative analysis

Quantitative analysis involves using mathematical and statistical techniques to measure, model, and understand aspects of human behavior.

A single study has more limitations. A meta-analysis provides more robust results that can help psychology researchers better understand the magnitude of an effect.

Purpose of a Meta-Analysis

In addition to summarizing and analyzing integrated results, a meta-analysis can have other important objectives. Psychology researchers might use this type of research to:

• Evaluate effects in different subsets of participants
• Create new hypotheses to inspire future studies
• Overcome the limitations of small sample sizes
• Establish statistical significance

Increasing Sample Size

One of the reasons why meta-analyses are so useful is because of an all too common problem across many research studies: small sample sizes.

Using a large sample size requires more resources, including funds and personnel, than a small sample size. When individual research projects don't study a significant number of subjects, it can be difficult to draw reliable and valid conclusions. 

Establishing Statistical Significance

Meta-analyses can also help establish statistical significance across studies that might otherwise seem to have conflicting results.

When you take many studies into consideration at once, the statistical significance established is much greater than with one study alone. This is important because statistical significance increases the validity of any observed differences. This increases the reliability of the information.

Benefits of a Meta-Analysis

Meta-analyses offer numerous advantages over individual studies. Some key advantages include:

• Greater statistical power and more ability to extrapolate to the greater population
• Evidence-based
• More likely to observe an effect, due to combining smaller studies into one larger study
• Increased accuracy, because smaller studies are pooled and analyzed
• Efficiency (researchers can collect a large amount of data without spending a lot of time, money, and resources since the bulk of the data collection work has already been completed)

Meta-analysis provides a view of the research that has been done in a particular field, summarizes and integrates different findings, and provides important directions for future research.

A meta-analysis also reduces the amount of work required to research a topic for other researchers and policy-makers. Instead of having to look at the results of many different smaller studies, people can instead get a more accurate view of what might be happening in a population by looking at the meta-analysis results.

Disadvantages

Although a powerful research tool, meta-analysis does have some disadvantages. It can be difficult and time-consuming to find all of the appropriate studies to examine.

Meta-analyses also require complex statistical skills and techniques. This can be intimidating and challenging for researchers who may lack experience with this type of research.

Some researchers have suggested that a meta-analysis often has the effect of halting research on a particular topic. Rather than giving directions for future research, it may imply that a specific question has been answered and is not in need of additional inquiry.

Types of Bias

While researchers acknowledge that a meta-analysis is an effective tool, researchers' procedures may impact their results. Following certain principles is critical to drawing valid and reliable conclusions.

Even minor deviations from protocol can produce biased and misleading results. The three main types of bias are:

1. Publication bias: "Positive" studies are more likely to go to print.
2. Search bias: The search for studies can produce unintentionally biased results. This includes using an incomplete set of keywords or varying strategies to search databases. Also, the search engine used can be a factor.
3. Selection bias: Researchers must clearly define criteria for choosing from the long list of potential studies to be included in the meta-analysis to ensure unbiased results.

Examples of Meta-Analysis in Psychology

It can be helpful to look at how a meta-analysis might be used in psychology to research specific topics. For example, imagine that a small study showed that consuming sugar before an exam was correlated to decreased test performance.

Taken alone, such results would imply that students should avoid sugar consumption before taking an exam. However, a meta-analysis that pools data looking at eating behavior and subsequent test results might demonstrate that this previous study was an outlier.

A Word From Verywell

A meta-analysis can be a useful research tool in psychology. In addition to providing a more accurate look at a specific topic, such studies often make it easier for policy-makers and other decision-makers to see a summary of findings more quickly.