Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Investigación Causal-Comparativa Transversal× | Investigación Causal-Comparativa× | |
|---|---|---|
| Campo | Diseño de investigación | Diseño de investigación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1960s onward | 1964 |
| Autor original≠ | Donald T. Campbell and Julian C. Stanley (quasi-experimental foundations); refined in education research by various methodologists | Fred N. Kerlinger |
| Tipo≠ | Non-experimental quantitative design | Non-experimental quantitative research design |
| Fuente seminal≠ | Frankfort-Nachmias, C., & Nachmias, D. (2015). Research Methods in the Social Sciences (8th ed.). Worth Publishers. ISBN: 978-1429295154 | Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston. link ↗ |
| Alias | cross-sectional ex post facto design, single-wave causal-comparative study, cross-sectional group-comparison design, cross-sectional criterion-group study | ex post facto research, causal-comparative design, retrospective causal study, CCR |
| Relacionados | 3 | 3 |
| Resumen≠ | Cross-sectional causal-comparative research compares two or more pre-existing groups — defined by a characteristic or experience that has already occurred — on one or more outcome variables, with all data collected at a single point in time. Because the presumed cause (group membership) precedes measurement but cannot be manipulated, the design sits between purely descriptive and truly experimental work. It is widely used in education, psychology, and social sciences when randomization is impossible or unethical. | 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. |
| ScholarGateConjunto de datos ↗ |
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