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| Hierarchikus kauzális-komparatív kutatás× | Kauzális-komparatív kutatás× | |
|---|---|---|
| Tudományterület | Kutatástervezés | Kutatástervezés |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 1960s (causal-comparative); 1980s–2002 (hierarchical/multilevel extension) | 1964 |
| Megalkotó≠ | Kerlinger (causal-comparative logic); Raudenbush & Bryk (hierarchical extension) | Fred N. Kerlinger |
| Típus | Non-experimental quantitative research design | Non-experimental quantitative research design |
| Alapmű≠ | 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. link ↗ |
| Alternatív nevek | 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 |
| Kapcsolódó≠ | 4 | 3 |
| Összefoglaló≠ | 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. |
| ScholarGateAdatkészlet ↗ |
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