Conditiondependent

Conditiondependent is an adjective used to describe phenomena, measurements, or relationships that vary depending on one or more specified conditions. The term is commonly written condition-dependent, but conditiondependent also appears in some texts and data labels.

In statistics and data analysis, a variable is conditionally dependent on another when its distribution or outcome changes when conditioning on that variable. This idea underpins conditional probability, conditional expectation, and models that include interaction terms. Recognizing condition dependence helps clarify how context or conditions shape observed results.

In biology and ecology, condition-dependent traits are expressions that depend on environmental or internal state, such as temperature, nutrition, or stress. Condition dependence reflects phenotypic plasticity and can influence fitness, behavior, and ecological interactions. It explains why the same genotype may produce different phenotypes under different conditions.

In experimental design, researchers assess condition dependence by controlling or varying the conditioning factors, stratifying data by the condition, or adding interaction terms in regression models. Failure to account for condition dependence can lead to biased conclusions or incorrect generalizations.

Examples include seed germination rates that increase with adequate moisture, disease risk that depends on climate, or gene–environment interactions where genetic effects vary with environmental context. Understanding condition dependence supports more accurate inference about causal relationships and the robustness of observed effects.

See also conditional probability, conditional distribution, regression with interaction, phenotypic plasticity, and gene–environment interaction.