Meta-analytics - literature analysis

Meta-analysis is a statistical synthesis of results from multiple studies that address a sufficiently comparable question. A systematic review may include meta-analysis, but a literature summary is not automatically a meta-analysis. The distinction matters because combining incompatible or selectively chosen studies can create a more precise-looking error.

When to use it

Use synthesis when relevant research already exists and a structured review can answer the question more credibly or economically than one new study alone.

It can help explore:

• What is known about trends in market X?
• How might customer behaviour change, and how certain is that conclusion?
• What role might mobile computing play in the industry?
• Which factors are consistently associated with staff engagement?

A formal meta-analysis is suitable only when studies report compatible outcomes and enough statistical information. Otherwise use a transparent systematic or scoping review.

Origins

Research synthesis has roots in statistical work that predates the modern label. Gene Glass later introduced “meta-analysis” for the analysis of results across analyses, and health and social science organisations subsequently developed protocols for systematic searches, bias assessment and quantitative pooling. The method has no single universal recipe; design depends on the question, evidence and effect measure.

What it is

A meta-analysis estimates a combined effect from individual study estimates, weighted by their uncertainty under a stated statistical model. It can show variation among studies, explore moderators and make disagreement visible. It does not literally combine every study ever conducted, and it cannot repair biased, irrelevant or poorly measured inputs.