Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Многомерное когортное исследование× | Лонгитюдное исследование× | |
|---|---|---|
| Область | Дизайн исследования | Дизайн исследования |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1950s–1970s (cohort methods); multivariate extensions prominent from 1970s onward | Late 19th–early 20th century; methodologically codified through the 20th century |
| Автор метода≠ | Epidemiology and biostatistics tradition; advanced by Rothman, Breslow, and colleagues | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Тип≠ | Observational quantitative research design | Quantitative (or mixed) observational research design |
| Основополагающий источник≠ | 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 |
| Другие названия | 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 |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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