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Cross-sectional studies (also know as Cross-sectional analysis) form a class of research methods that involve observation of some subset of a population of items all at the same time.
The alternative is longitudinal studies.
A cross-sectional study is a study in which disease and exposure status are measured simultaneously in a given population. Cross-sectional studies can be thought of as providing a "snapshot" of the frequency and characteristics of a disease in a population at a particular point in time. This type of data can be used to assess the prevalence of acute or chronic conditions in a population. However, since exposure and disease status are measured at the same point in time, it may not always be possible to distinguish whether the exposure preceded or followed the disease. The cross-sectional survey--which, like a snapshot, "freezes" a specific moment in time--aims at finding the same kind of relationships that might be shown by the "moving picture" of the cohort study, but at far less cost. In a cross-sectional survey, a specific group is looked at to see if a substance or activity, say smoking, is related to the health effect being investigated--for example, lung cancer. If a significantly greater number of smokers already have lung cancer than those who don't smoke, this would support the hypothesis that lung cancer is caused by smoking.
Cross-sectional analysis studies the relationship between different variables at a point in time. For instance, the relationship between income, locality, and personal expenditure. Unlike time series, cross-sectional analysis relates to how variables affect each other at the same time.
de:Querschnitt (empirische Forschung) sv:Tvärsnittstudie zh:横断面研究
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