השוואת שיטות

	מחקר מאשש השוואתי	מחקר מאשר
תחום	תכנון מחקר	תכנון מחקר
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1971 (Jöreskog); systematized in organizational research by 2000	1934 (Popper); widely adopted in social sciences from 1960s onward
הוגה השיטה	Karl Jöreskog (multigroup CFA foundation); Robert Vandenberg & Charles Lance (organizational application)	Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others
סוג	Quantitative comparative research design	Quantitative research design
מקור מכונן	Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70.	Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson. ISBN: 978-0415278447
כינויים	multigroup confirmatory research, cross-group confirmatory study, comparative hypothesis testing design, comparative model testing research	hypothesis-testing research, deductive research, theory-testing research, confirmatory study
קשורות	4	4
תקציר	Comparative confirmatory research tests whether a pre-specified theoretical model or set of hypotheses holds equivalently across two or more distinct groups, time points, or contexts. It extends standard confirmatory analysis by explicitly imposing and evaluating equality constraints across groups, determining not only whether a model fits the data but whether its structure, factor loadings, and parameter estimates are comparable across populations. This design is foundational to cross-cultural, multi-site, and subgroup comparison studies.	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.