Σύγκριση μεθόδων

	Έρευνα Ελέγχου Μοντέλων	Έρευνα Ελέγχου Υποθέσεων
Πεδίο	Ερευνητικός Σχεδιασμός	Ερευνητικός Σχεδιασμός
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s	Early 20th century (Fisher 1925; Neyman–Pearson 1933)
Δημιουργός	Karl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition	Karl Pearson, Ronald A. Fisher, Jerzy Neyman, Egon Pearson
Τύπος	Confirmatory quantitative research design	Quantitative confirmatory research design
Θεμελιώδης πηγή	Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344	Kerlinger, F. N., & Lee, H. B. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417603
Εναλλακτικές ονομασίες	model-based research, structural model testing, theory-testing research, MTR	hypothetico-deductive research, confirmatory quantitative research, null hypothesis significance testing, NHST design
Συναφείς	5	4
Σύνοψη	Model testing research is a confirmatory quantitative design in which the researcher specifies a theoretical model — depicting hypothesized relationships among constructs — and then tests how well that model fits empirical data. Drawing primarily on structural equation modeling (SEM) and confirmatory factor analysis (CFA), it evaluates whether the data-implied covariance structure is consistent with the theoretically derived one, yielding fit indices that indicate model-data correspondence.	Hypothesis testing research is a quantitative design in which the investigator derives one or more explicit, falsifiable propositions from theory, translates them into a null hypothesis (H0) and an alternative hypothesis (H1), collects empirical data, and then applies an inferential statistical test to decide whether the evidence is sufficient to reject H0. The approach is the dominant paradigm for confirmatory science across the social, behavioral, health, and natural sciences.