prespecified

Prespecified is an adjective describing something defined or determined in advance of a particular event, condition, or analysis. The term is commonly used in scientific and technical contexts to distinguish planned elements from those identified after observing data or results. In everyday language, prespecified requirements or parameters are fixed before actions or investigations take place.

In research and statistics, prespecified endpoints, hypotheses, and analysis plans are declared before data collection begins. Prespecification helps prevent data dredging and selective reporting, supporting objectivity, reproducibility, and credible conclusions. Regulatory bodies often require prespecified primary analyses and endpoints in clinical trials; deviations must be transparently disclosed and justified. Exploratory analyses remain valuable for generating new hypotheses but are typically considered separate from confirmatory, prespecified analyses.

In statistics and data science, prespecified parameters or constraints may refer to values fixed prior to model fitting or inference, such as the form of a model, priors in Bayesian analysis, or selected covariates. In computational and engineering contexts, prespecification can apply to input ranges, configuration settings, tolerances, or performance criteria established before implementation or production.

The concept is closely related to preregistration, prespecified hypotheses, and a priori reasoning. It underscores the distinction between planned analyses or specifications and post hoc adjustments driven by observed data, contributing to transparency and methodological rigor.