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. 2010 Mar;107(11):187-92.
doi: 10.3238/arztebl.2010.0187. Epub 2010 Mar 19.

Data analysis of epidemiological studies: part 11 of a series on evaluation of scientific publications

Meike Ressing  1 , Maria Blettner, Stefanie J Klug
Affiliations

Data analysis of epidemiological studies: part 11 of a series on evaluation of scientific publications

Meike Ressing et al. Dtsch Arztebl Int. 2010 Mar.

Abstract

Introduction: An important objective of epidemiological research is to identify risk factors for disease. Depending on the particular question being asked, cohort studies, case-control studies, or cross-sectional studies are conducted.

Methods: Methods of data analysis in different types of epidemiological studies are illustrated through examples with fictive data. Important measures of frequency and effect will be introduced. Different regression models will be presented as examples of complex analytical methods.

Results: Important frequency measures in cohort studies are incidence and mortality. Important effect measures such as the relative risk (RR), hazard ratio (HR), standardized incidence ratio (SIR), standardized mortality ratio (SMR), and odds ratio (OR) can also be calculated. In case-control or cross-sectional studies, the OR can be calculated as an effect measure. In cross-sectional studies, prevalence is the most important frequency measure. The interpretation of different frequency measures and effect measures will be discussed.

Conclusion: The measures to be calculated and the analyses to be performed in an epidemiological study depend on the research questions being asked, the study type, and the available data.

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Figures

Figure
Figure
Important epidemiological frequency measures and comparative measures; *1 per 100 000, *2 per cent
See this image and copyright information in PMC

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