overrepresented

Overrepresented is an adjective describing a group whose share in a sample exceeds what would be expected based on a reference population. It is used in statistics, epidemiology, sociology, and related fields to flag a pattern where a category occurs more frequently than anticipated. The term is one aspect of disproportionality; the opposite condition is underrepresented.

Assessment typically compares observed counts with expected counts under a null model, using metrics such as rate ratios, risk ratios, odds ratios, or standardized incidence ratios. Statistical tests like the chi-square test or Fisher’s exact test quantify whether the deviation is unlikely to occur by chance. In some disciplines, disproportionality analyses or standardized measures are customized for specific data, such as pharmacovigilance or health surveillance.

Examples include epidemiology, where a disease might be overrepresented in a subpopulation relative to the overall population; genetics, where an allele is more common in a subpopulation due to ancestry; or social science, where a demographic group appears more frequently in certain outcomes because of structural factors. Overrepresentation can thus reflect true differences in risk or exposure, as well as biases in sampling, reporting, or measurement.

Interpretation requires careful consideration of confounding, sampling bias, and population structure. Overrepresentation does not by itself imply causation and can be influenced by data quality and design. Proper analysis often involves stratification, multivariable modeling, or sensitivity analyses to separate genuine disparities from artifacts. See also underrepresentation and disproportionality.