Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Estudi de cohort× | Disseny d'investigació per enquesta× | |
|---|---|---|
| Camp≠ | Epidemiologia | Disseny de recerca |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | Mid-20th century (formal epidemiological design codified ~1950s) | Late 19th century; methodologically systematised 1940s–1960s |
| Autor original≠ | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) | Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s |
| Tipus≠ | Observational longitudinal study design | Quantitative (and mixed) non-experimental design |
| Font seminal≠ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 | Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000 |
| Àlies | longitudinal study, follow-up study, panel study, incidence study | survey methodology, questionnaire research, survey design, survey study |
| Relacionats≠ | 6 | 4 |
| Resum≠ | A cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome. | Survey research is a quantitative (and sometimes mixed-methods) design in which a researcher collects standardised self-report data from a sample drawn from a defined population, using a questionnaire or structured interview. It is the dominant non-experimental strategy for describing population characteristics, estimating prevalence, mapping attitude distributions, and testing bivariate or multivariate associations across social, behavioural, and health sciences. |
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