Nonindependent

Nonindependent is an adjective describing something that is not independent; lacking autonomy or agency, or not deriving from itself but rather from other sources. In everyday usage, it can refer to persons, organizations, or entities that rely on another for support, governance, or decision-making, and therefore do not possess full autonomy. In political science and law, nonindependent is sometimes used to describe states, regions, or territories that are not sovereign or self-governing, often under the authority of another country or central government.

In statistics and research design, nonindependence (or the nonindependent nature of observations) refers to violations of the assumption that observations are independent. This arises from clustering, repeated measures on the same unit, familial or environmental sharing, or temporal proximity. Nonindependence inflates type I error rates and biases standard errors if not addressed. Analysts address it by using mixed-effects or multilevel models that incorporate random effects, generalized estimating equations that specify correlation structures, robust standard errors clustered at the appropriate level, or resampling methods designed for dependent data. Proper experimental design and analysis require recognizing and accounting for dependence to obtain valid inferences.

While the term nonindependent is valid, it is more common to discuss independence or dependence, or to describe the specific source of dependence (e.g., spatial, temporal, or hierarchical dependence). See also: independence, dependence, nonindependence of observations, multilevel modeling.