Primary and secondary data, including meta-analysis.

The idea

Primary data is gathered first-hand by the researcher, for this investigation's own aim, through an experiment, questionnaire, interview or observation. Secondary data already exists: somebody else collected it, usually for another purpose, as with government statistics, medical records or a published study. Primary data fits the hypothesis exactly but costs time and money; secondary data is cheap and immediate, though it may be outdated, incomplete or produced under conditions you cannot check. A meta-analysis is the disciplined use of secondary data: results from many studies of one question are pooled and an effect size, a standardised measure of how strong the finding is, lets studies of different sizes be compared. Van IJzendoorn and Kroonenberg pooled 32 Strange Situation studies and found variation within countries larger than between them.

What earns the marks

• Primary data: collected first-hand by the researcher for the current aim.
• Secondary data: already in existence, collected by another person, often for a different purpose.
• Strength of primary data: it targets the hypothesis, and the researcher controls the conditions under which it was produced.
• Strengths of secondary data: inexpensive, immediately available and often drawn from far larger samples than one researcher could gather.
• Meta-analysis defined as the statistical pooling of results from many studies of the same question, with an effect size calculated as a standardised measure of the strength of the finding.
• Evaluation of meta-analysis: the combined sample is huge, so generalisability improves, but publication bias means non-significant studies are less likely to be in print and the pooled effect can be inflated.

Common mistakes and how to put them right

• Labelling every published study as secondary data.

  Put it right: A study is primary data for the team that ran it and secondary only for the researcher who later reuses it.

• Defining meta-analysis as 'a review of lots of studies', which describes a literature review.

  Put it right: The defining feature is that the results are combined and analysed statistically.

• Omitting effect size altogether, which is the term the examiner is looking for.

• Asserting that secondary data is always less valid, when official statistics are often collected far more rigorously than a single researcher could manage.

Exam tips

• Settle primary versus secondary on who collected it and for what aim, not on how old the data is.
• For a four-mark 'outline and evaluate meta-analysis', one clean definition plus one developed strength and one developed limitation beats four undeveloped points.
• Name the evaluative problem, such as publication bias or differences in method between the pooled studies, rather than writing that the findings 'might not be accurate'.