Jämför metoder

	Hierarkisk kausal-jämförande forskning	Kausal-komparativ forskning – Retrospektiv gruppjämförelsestudie
Ämnesområde	Forskningsdesign	Forskningsdesign
Familj	Process / pipeline	Process / pipeline
Ursprungsår	1960s (causal-comparative); 1980s–2002 (hierarchical/multilevel extension)	1964
Upphovsperson	Kerlinger (causal-comparative logic); Raudenbush & Bryk (hierarchical extension)	Fred N. Kerlinger
Typ	Non-experimental quantitative research design	Non-experimental quantitative research design
Ursprungskälla	Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049	Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston.
Alias	multilevel causal-comparative design, nested causal-comparative research, HLM causal-comparative study, hierarchical ex post facto comparison	ex post facto research, causal-comparative design, retrospective causal study, CCR
Närliggande	4	3
Sammanfattning	Hierarchical causal-comparative research is a non-experimental quantitative design that compares pre-existing groups on an outcome variable while explicitly modeling the nested structure of the data. Participants are clustered within higher-level units — students within classrooms, employees within organizations — and the design uses multilevel analytical techniques to distinguish group differences at each level. The cause-and-effect inference is strengthened by accounting for variance attributable to the hierarchy rather than misattributing it to individual-level group membership.	Causal-comparative research is a non-experimental quantitative design in which the researcher compares two or more groups that already differ on an independent variable — one that was not manipulated — to investigate possible causes or consequences of that difference. Because group membership is pre-existing rather than randomly assigned, the design can suggest causal relationships but cannot establish them with the certainty of a true experiment. It is widely used in education, psychology, and social sciences when experimental manipulation is impractical or unethical.