Salīdzināt metodes

	Eksperimentālā dizaina un analīzes devas-atbildes sakarība	ANOVA ar atkārtotiem mērījumiem
Nozare	Eksperimentu plānošana	Statistika
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1994	1992
Autors	Classical pharmacology; formalized by ICH E4 (1994) and Ritz et al. (2015)	Girden (textbook treatment); Field (2013)
Tips	Nonlinear curve fitting and monotone contrast testing	Parametric within-subjects mean comparison
Pirmavots	Ritz, C., Baty, F., Streibig, J. C., & Gerhard, D. (2015). Dose-Response Analysis Using R. PLOS ONE, 10(12), e0146021.	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185
Citi nosaukumi	dose-response analysis, dose-response curve, Doz-Yanıt Tasarımı ve Analizi (Dose-Response), ED50 analysis	within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA
Saistītās	4	4
Kopsavilkums	Dose-response design is a framework for planning and analysing experiments that characterise the relationship between the amount of a stimulus — such as a drug dose or a chemical concentration — and the magnitude of a biological or physiological response. Formalised in regulatory guidance by the ICH E4 guideline (1994) and extensively developed in the statistical literature by Ritz et al. (2015), the framework covers experiment design, four-parameter and five-parameter logistic curve fitting, key benchmark estimates (ED50/EC50, NOAEL, LOAEL), and monotone trend testing via the Williams procedure.	Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013).