Confronta i metodi

	Differenza Minima Importante Basata su Ancore	Analisi Fattoriale per lo Sviluppo di Scale
Campo	Psicometria	Psicometria
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	1989	1947
Ideatore	Guyatt, Jaeschke, and Singer	Louis Thurstone
Tipo	Minimal clinically important difference estimation	Exploratory factor analysis methodology
Fonte seminale	Jaeschke, R., Singer, J., & Guyatt, G. H. (1989). Measurement of health status: Ascertaining the minimal clinically important difference. Controlled Clinical Trials, 10(4), 407-415.	Thurstone, L. L. (1947). Multiple-Factor Analysis: A Development and Expansion of the Vectors of Mind (2nd ed.). Chicago: University of Chicago Press. ISBN: 9780226797557
Alias	MCID, Minimal clinically important difference, Anchor-based MCID, Minimal important change	Exploratory factor analysis, EFA for scale development, Factorial structure analysis
Correlati	4	5
Sintesi	The anchor-based method for establishing Minimal Clinically Important Difference (MCID) is a technique for determining the smallest change in a patient-reported outcome (PRO) that patients or clinicians perceive as meaningful or important. Pioneered by Guyatt, Jaeschke, and Singer in 1989, this approach anchors changes in outcome scores to external clinically meaningful events or judgments, enabling researchers and clinicians to interpret whether treatment effects represent real, patient-relevant improvements.	Exploratory factor analysis (EFA) is a statistical method for discovering the underlying dimensional structure of a set of items or variables. Pioneered by Louis Thurstone in the mid-20th century, EFA is widely used to develop and validate psychometric scales by identifying groups of items that correlate together, thereby revealing latent dimensions of the construct being measured. The method reduces item sets to a smaller number of interpretable factors.