Vertaile menetelmiä

	Risk-adjusted Nested Case-Control	Sisäkkäinen tauti-verrokkitutkimus
Tieteenala	Epidemiologia	Epidemiologia
Menetelmäperhe	Process / pipeline	Process / pipeline
Syntyvuosi	1977 (nested case-control); risk-adjusted extensions 1980s–2000s	1973–1977
Kehittäjä	Thomas (1977) for nested case-control; risk adjustment extensions developed through pharmacoepidemiology literature (1980s–2000s)	Nathan Mantel (1973); D. C. Thomas (1977 formalization)
Tyyppi	Observational analytical study design	Hybrid observational study design
Alkuperäislähde	Thomas, D. C. (1977). Addendum to: Methods of cohort analysis: Appraisal by application to asbestos mining. Journal of the Royal Statistical Society, Series A, 140(4), 469–491.	Thomas, D. C. (1977). Addendum to: Methods of cohort analysis: Appraisal by application to asbestos mining. Journal of the Royal Statistical Society, Series A, 140(4), 469–491.
Rinnakkaisnimet	risk-adjusted NCC, covariate-adjusted nested case-control, propensity-score nested case-control, nested case-control with risk adjustment	NCC study, nested CC design, case-control within cohort, density sampling case-control
Liittyvät	4	6
Tiivistelmä	A risk-adjusted nested case-control study embeds a case-control comparison inside a defined cohort and explicitly accounts for differences in baseline risk between cases and controls through covariate adjustment — most commonly via risk scores, propensity scores, or stratification. It preserves the efficiency advantages of the nested design while reducing confounding attributable to pre-existing risk differentials, making it especially valuable in pharmacoepidemiology and clinical effectiveness research.	A nested case-control study is an efficient observational design embedded within a defined cohort. For each participant who develops the outcome of interest (a case), a small number of matched controls are sampled from those still at risk at the same point in time. This density-sampling strategy yields odds ratios that approximate incidence-rate ratios from the full cohort at a fraction of the data-collection cost — making it the preferred alternative when measuring exposures for all cohort members would be prohibitively expensive or technically demanding.