Salīdzināt metodes

	Konfirmatīvā pētījumu hierarhiskā analīze	Apstiprinošā pētniecība
Nozare	Pētījuma dizains	Pētījuma dizains
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1980s–2000s	1934 (Popper); widely adopted in social sciences from 1960s onward
Autors	Raudenbush & Bryk; Hox; Goldstein	Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others
Tips	Quantitative confirmatory research design	Quantitative research design
Pirmavots	Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049	Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson. ISBN: 978-0415278447
Citi nosaukumi	multilevel confirmatory research, nested confirmatory design, hierarchical hypothesis-testing research, HCR	hypothesis-testing research, deductive research, theory-testing research, confirmatory study
Saistītās	5	4
Kopsavilkums	Hierarchical confirmatory research is a quantitative design that tests pre-specified hypotheses about relationships or group differences in data that have a natural nested (hierarchical) structure — such as students clustered within classrooms, patients within hospitals, or employees within organizations. By explicitly modeling the hierarchy, it avoids the inflation of Type I error that occurs when nested data are analyzed as though observations were independent.	Confirmatory research is a deductive quantitative design in which the researcher specifies hypotheses derived from existing theory before data collection, then tests whether the data support or refute those hypotheses. Unlike exploratory approaches that generate ideas from data, confirmatory research begins with an established theoretical framework, pre-registers predictions, and applies statistical tests to evaluate those predictions against empirical evidence. It is the backbone of hypothesis-driven social, behavioral, and health science inquiry.