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Дизайн "случай-перекрестный" с поправкой на риск×Когортное исследование с поправкой на риск×
ОбластьЭпидемиологияЭпидемиология
СемействоProcess / pipelineProcess / pipeline
Год появления1991 (base design); risk-adjustment extensions from mid-1990s onwardMid–late 20th century (risk-adjusted cohort designs systematized by 1970s–1990s)
Автор методаMalcolm Maclure (case-crossover base); extensions incorporating covariate risk adjustment developed in subsequent pharmacoepidemiology literatureEvolution of cohort study methodology; risk adjustment formalized through work of Rothman, Greenland, and others in epidemiology, 20th century
ТипObservational analytic epidemiological designObservational epidemiological study design with statistical confounding control
Основополагающий источникMaclure, M. (1991). The case-crossover design: a method for studying transient effects on the risk of acute events. American Journal of Epidemiology, 133(2), 144–153. DOI ↗Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641
Другие названияadjusted case-crossover study, covariate-adjusted case-crossover, risk-controlled case-crossover, case-crossover with risk adjustmentadjusted cohort study, covariate-adjusted cohort, risk-controlled prospective study, propensity-adjusted cohort
Связанные44
СводкаThe risk-adjusted case-crossover design is a self-matched epidemiological method that compares a person's exposure during a brief hazard window immediately preceding an acute event to their exposure during one or more control windows from the same individual, while formally accounting for time-varying or time-fixed covariates that could confound the exposure-event relationship. By using each case as their own control, stable individual-level confounders are automatically cancelled, while covariate adjustment handles residual time-varying risks.A risk-adjusted cohort study is an observational epidemiological design in which a defined group of individuals is followed over time to compare outcomes between exposed and unexposed subgroups, with statistical methods applied to control for measured confounders. Adjustment strategies — including multivariable regression, propensity score matching, inverse probability weighting, or standardization — are used to reduce bias and produce effect estimates that more closely approximate what would be observed in a randomized trial.
ScholarGateНабор данных
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  3. PUBLISHED
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ScholarGateСравнение методов: Risk-adjusted case-crossover design · Risk-adjusted cohort study. Получено 2026-06-19 из https://scholargate.app/ru/compare