Linganisha mbinu

	Ubunifu na Uchambuzi wa Majaribio ya Kiwango-Majibu	ANOVA ya Vipimo Rudia
Nyanja	Muundo wa Majaribio	Takwimu
Familia	Hypothesis test	Hypothesis test
Mwaka wa asili	1994	1992
Mwanzilishi	Classical pharmacology; formalized by ICH E4 (1994) and Ritz et al. (2015)	Girden (textbook treatment); Field (2013)
Aina	Nonlinear curve fitting and monotone contrast testing	Parametric within-subjects mean comparison
Chanzo asilia	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
Majina mbadala	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
Zinazohusiana	4	4
Muhtasari	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).