Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Recherche transversale comparative× | Recherche causale-comparative× | |
|---|---|---|
| Domaine | Conception de la recherche | Conception de la recherche |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | Mid-20th century (widely formalized from 1950s onward) | 1964 |
| Auteur d'origine≠ | Epidemiological tradition; formalized in observational study typologies | Fred N. Kerlinger |
| Type≠ | Observational quantitative design | Non-experimental quantitative research design |
| Source fondatrice≠ | Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195083507 | Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston. link ↗ |
| Alias | comparative cross-sectional survey, cross-sectional comparative study, multi-group cross-sectional design, cross-sectional group comparison | ex post facto research, causal-comparative design, retrospective causal study, CCR |
| Apparentées | 3 | 3 |
| Résumé≠ | Comparative cross-sectional research is a quantitative observational design that measures and compares characteristics, attitudes, or outcomes across two or more pre-defined groups at a single point in time. By building the comparison into the sampling frame rather than treating it as a secondary analysis step, the design yields group-level contrasts without requiring follow-up measurement, making it efficient for describing between-group differences in prevalence, mean levels, or associations. | 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. |
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