The etymology of the Greek word Meta denotes “transcendence” or “comprehensive. Meta-analysis is the statistical analysis of numerous scientific studies that cater to a specific research question. It is a systematic analysis of the results of various scientific studies on a particular topic. The purpose of meta-analysis is to create a statistical pool of studies for analysis and evaluation. Researchers combine the results of various studies conducted by multiple researchers at different times and settings. The purpose is to draw a coherent conclusion from the results and findings of numerous studies. But meta-analysis is not appropriate for every type of research. Researchers must be aware of when and where to use it. This article will tell you when and where should you use meta-analysis.
What Is Meta-Analysis?
Meta-analysis refers to the systematic review and evaluation of scientific studies. Researchers combine the quantitative studies from several sources. The purpose of meta-analysis is to systematically review the results of various studies with the help of statistical tools. It helps the researcher develop a strong conclusion that has sufficient statistical significance. It is because the analysis involves multiple studies on a specific research topic. The combined analysis of these studies provides a comprehensive analysis and helps the researchers arrive at coherent conclusions. Most of students take it as difficult and hence hire UK dissertation writing services.
When And Where Should You Use Meta-Analysis?
Meta-analysis is akin to comparing oranges and apples. But it does not mean that the outcomes are invalid. This systematic analysis aims to synthesise the data from homogenous scientific studies. It is useful when the researcher’s goal is to broaden the understanding of the subject through synthesis. Also, it helps researchers extend the questions and analyse the patterns among the results. The usage of meta-analysis in research depends upon the researcher’s intent, aims and objectives. It helps researchers achieve the following goals:
- It is helpful when the research aims to integrate results from similar studies.
- It is useful when the researcher aims to estimate the combined effect of all studies.
- It is helpful when the researcher aims to report the summary effect.
- It is valuable when the researcher’s goals are to understand the dispersion in results across similar studies.
Policymaking in Interventionist Studies
You should use meta-analysis when single studies cannot inform the policy-making process. Clinical studies require intervention and formulation of policies based on thorough research. Single research cannot inform the decision-making process in clinical studies. Meta-analysis provides a broader perspective than the results of single studies. Researchers and policymakers can comprehend the overall effect across studies and its variability due to meta-analysis. It allows them to make better decisions about key policy topics. Evidence-based policy decisions, especially in medicine, require the employment of systematic studies to inform policymaking. Clinical and social interventions are not possible based on single study results.
You should only use meta-analysis when there is homogeneity across the study subjects, interventions and outcomes. Homogeneity has an integral role in meta-analysis to arrive at meaningful results. Although homogeneity does not mean that the results of various studies should be similar, they are bound to differ. But the studies should be identical regarding research design and other factors. Studies that are different in research design led to incoherent summary results. However, the heterogeneity in research design in the pool of various sources can lead to interesting insights. It depends upon the aims and objectives of the research.
Increase the Sample Size
Individual research studies have small sample sizes due to the limited scope of the research. The small sample size is also due to the limited financial resources and time constraints. Large sample size for a single study is impossible because it requires more resources such as capital, personnel, and equipment. It is also very time-consuming. Interventionist studies such as clinical psychology or public policy cannot draw reliable and valid conclusions. They cannot make appropriate decisions based on the findings of single studies. So, meta-analysis is useful and solves the problem of large sample sizes. When researchers combine the results of various studies for statistical analysis, it increases the sample size. Researchers can draw meaningful insights and reliable findings to inform the interventionist practices in clinical psychology and public policy.
Consolidate Statistical Significance
Meta-analysis is useful when the analysis aims to establish statistical significance across the contradictory results of various studies. Statistical significance unifies the findings from multiple studies and integrates them into a unified statement to predict the outcomes. Statistical significance increases the validity of the results. Researchers can be confident that the systematic analysis findings correspond to the investigated phenomenon’s real properties.
Analyse the Combined Effect of a Cause
Researchers should use meta-analysis when the purpose is to find the combined effect (mean effect) of a particular cause. Researchers pool different studies and perform a statistical analysis to see their combined effect. It leads to increased accuracy and efficiency.
Save Time and Money
You can use meta-analysis as a researcher when you want to save time and money. Individual examination of single studies separately is time-consuming and expensive. You can pool different studies to increase your understanding of a particular phenomenon. It helps you save time because data is already present, and you only have to analyse it.
Prelude to Future Research
Meta-analysis is an effective way to plan future studies. A systematic and thorough analysis of the research can help you identify the gaps in the research. You can determine which aspects of the specified topic are developed and which areas require further research. A systematic analysis can help you devise research questions and hypotheses for future research. It also increases your credibility as a researcher that you are familiar with the body of evidence.
The usage of meta-analysis in research depends upon the needs of the researcher and the nature of the research problem. It can help you summarise the research results through statistical analysis. It helps inform the policy-making and decision-making process in clinical and social interventions. Also, it allows you to summarise the study results and provide the basis for future research.