Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Ricerca di coorte multivariata× | Ricerca Longitudinale× | |
|---|---|---|
| Campo | Disegno della ricerca | Disegno della ricerca |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1950s–1970s (cohort methods); multivariate extensions prominent from 1970s onward | Late 19th–early 20th century; methodologically codified through the 20th century |
| Ideatore≠ | Epidemiology and biostatistics tradition; advanced by Rothman, Breslow, and colleagues | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Tipo≠ | Observational quantitative research design | Quantitative (or mixed) observational research design |
| Fonte seminale≠ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Alias | multivariate cohort study, cohort study with multivariate analysis, multivariable cohort design, multivariate longitudinal cohort | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Correlati≠ | 5 | 4 |
| Sintesi≠ | 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. | Longitudinal research is an observational design in which the same participants, groups, or units are measured repeatedly over an extended period. Rather than capturing a single snapshot, it tracks change, stability, and temporal sequencing of variables — making it the primary non-experimental strategy for studying development, growth, decline, and the unfolding of causal processes across time. |
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