In medical research, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis , transverse study , prevalence study ) is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time —that is, cross-sectional data.

In economics, cross-sectional studies typically involve the use of cross- sectional regression, in order to sort out the existence and magnitude of causal effects of one independent variable upon a dependent variable of interest at a given point in time. They differ from time series analysis, in which the behavior of one or more economic aggregates is traced through time.

In medical research, cross-sectional studies differ from case-control studies in that they aim to provide data on the entire population under study, whereas case-control studies typically include only individuals who have developed a specific condition and compare them with a matched sample, often a tiny minority, of the rest of the population. Cross-sectional studies are descriptive studies (neither longitudinal nor experimental). Unlike case- control studies, they can be used to describe, not only the odds ratio, but also absolute risks and relative risks from prevalences (sometimes called prevalence risk ratio , or PRR). They may be used to describe some feature of the population, such as prevalence of an illness, but cannot prove cause and effect. Longitudinal studies differ from both in making a series of observations more than once on members of the study population over a period of time.