Salīdzināt metodes

	Ekspertīze skrīninga testu novērtēšanai	Kaplan-Meier analīze
Nozare	Epidemioloģija	Epidemioloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1968 (Wilson-Jungner principles); statistical framework developed 1970s–2000s	1958
Autors	Wilson & Jungner (WHO criteria, 1968); foundational work by Pepe, Altman, and others in statistical test evaluation	Edward L. Kaplan and Paul Meier
Tips	Observational diagnostic / epidemiological evaluation design	Nonparametric survival estimator
Pirmavots	Wilson, J. M. G., & Jungner, G. (1968). Principles and Practice of Screening for Disease. World Health Organization. Public Health Papers No. 34.	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.
Citi nosaukumi	screening study, screening performance evaluation, screening accuracy assessment, STE	KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve
Saistītās	6	5
Kopsavilkums	Screening test evaluation is a systematic epidemiological approach for assessing whether a test or program can accurately and cost-effectively identify individuals with a condition before symptoms appear. It quantifies diagnostic performance metrics — sensitivity, specificity, predictive values, and the ROC curve — and evaluates whether a screening program meets established public health criteria for adoption and harm-benefit balance.	Kaplan-Meier (KM) analysis is a nonparametric method for estimating the survival function from time-to-event data. Introduced by Kaplan and Meier in 1958, it produces the classic step-function survival curve that shows the probability of surviving beyond each observed event time, correctly accounting for censored observations — participants who left the study or had not yet experienced the event by the end of follow-up. It is one of the most widely used techniques in clinical and epidemiological research.