Methoden vergleichen

	Ankerbasierte minimale wichtige Differenz	Faktorenanalyse zur Skalenentwicklung
Fachgebiet	Psychometrie	Psychometrie
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1989	1947
Urheber	Guyatt, Jaeschke, and Singer	Louis Thurstone
Typ	Minimal clinically important difference estimation	Exploratory factor analysis methodology
Wegweisende Quelle	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
Aliasnamen	MCID, Minimal clinically important difference, Anchor-based MCID, Minimal important change	Exploratory factor analysis, EFA for scale development, Factorial structure analysis
Verwandt	4	5
Zusammenfassung	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.