Salīdzināt metodes

	Pētījumi ar salīdzinošu modeļu testēšanu	Hipozēžu pārbaudes pētījumi
Nozare	Pētījuma dizains	Pētījuma dizains
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1969–2000s	Early 20th century (Fisher 1925; Neyman–Pearson 1933)
Autors	Rooted in structural equation modeling traditions; formalized through Jöreskog (1969) and extended by Vandenberg & Lance (2000)	Karl Pearson, Ronald A. Fisher, Jerzy Neyman, Egon Pearson
Tips	Quantitative confirmatory-comparative research design	Quantitative confirmatory research design
Pirmavots	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
Citi nosaukumi	comparative model comparison, cross-group model testing, competing model comparison research, comparative structural model evaluation	hypothetico-deductive research, confirmatory quantitative research, null hypothesis significance testing, NHST design
Saistītās	4	4
Kopsavilkums	Comparative model testing research is a quantitative design in which two or more theoretically motivated models — or the same model evaluated across distinct groups or conditions — are systematically tested and compared using fit indices, likelihood-ratio tests, or information criteria. The goal is to determine which model better represents the data structure, or whether a model's parameter structure holds equally across comparison groups.	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.