Meta Analysis

In general terms, meta analysis is the statistical procedure for combining data from multiple studies. It is a type of quantitative and formal study used to systematically assess the results of previous research. This is generally a part of medical data analysis and researches.

  • Conceptually it increases the power over individual studies and improves the estimate.
  • It yields a weighted average from the results of the individual studies.
  • It aggregates information leading to a higher statistical power from any individual study.
  • They are mostly a systematic review procedure.
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Advantages of Meta Analysis

Meta analysis, conceptually, uses a statistical approach to combine results from multiple studies, in order to increase the power over individual studies. While it improves the estimate size and resolve uncertainty in clinical treatments and reports, it overviews one or more systematic reviews.

  • Results can be of larger population.
  • Hypothesis testing can also be applied on the estimates.
  • Variations between the studies can be explained.
  • Inconsistency and uncertainty can be quantified and analysed.
  • Accuracy is improved as more data is used.

Limitations of Meta Analysis

When a good data analysis software is used, it doesn’t necessarily have benefits but also some limitations in it. However, most of the researchers have argued that better approach may be used but every approach may have a set of limitations in analysing the data as a good meta analysis may not correct poor design.

  • It does not predict results of a single large study.
  • The analysis have lesser number of available published studies.
  • Studies do not necessarily reach a statistical significance.
  • Separate meta-analyses for each imputed dataset is required.
  • The accuracy cannot be judged while combining the results.

Why choose our meta-analysis service?

While decisions about the validity of a hypothesis cannot be based on the results of a single study, because results typically vary in every study. A mechanism is always needed to synthesis data across the studies and while narrative review is preferred, it is more often impossible when more studies are involved. However, meta analysis fits at different areas in the research process and they are:

  • Publication
  • Grant application
  • Planning for new studies
  • Identifying which questions had been answered and which are to be answered
  • Replacing the traditional narrative approach
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