Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Investigación de cohortes multivariante× | Investigación Causal-Comparativa× | |
|---|---|---|
| Campo | Diseño de investigación | Diseño de investigación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1950s–1970s (cohort methods); multivariate extensions prominent from 1970s onward | 1964 |
| Autor original≠ | Epidemiology and biostatistics tradition; advanced by Rothman, Breslow, and colleagues | Fred N. Kerlinger |
| Tipo≠ | Observational quantitative research design | Non-experimental quantitative research design |
| Fuente seminal≠ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 | Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston. link ↗ |
| Alias | multivariate cohort study, cohort study with multivariate analysis, multivariable cohort design, multivariate longitudinal cohort | ex post facto research, causal-comparative design, retrospective causal study, CCR |
| Relacionados≠ | 5 | 3 |
| Resumen≠ | Multivariate cohort research follows a defined group of individuals forward in time, collecting data on multiple exposures, outcomes, and covariates simultaneously. By applying multivariate statistical models — such as Cox regression, mixed-effects models, or structural equation models — researchers can disentangle the independent contributions of several predictors to one or more outcomes while controlling for confounders. The design is widely used in epidemiology, public health, psychology, and social sciences. | 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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