Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Utafiti wa Kulinganisha-Kihusishi kwa Msingi wa Paneli× | Utafiti wa Cohort× | |
|---|---|---|
| Nyanja≠ | Muundo wa Utafiti | Epidemiolojia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1950s–1980s (formalized across educational and social science methodology literature) | Mid-20th century (formal epidemiological design codified ~1950s) |
| Mwanzilishi≠ | Building on causal-comparative tradition (John W. Best, 1959) extended to panel data structures in social and educational research | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) |
| Aina≠ | Quantitative observational research design | Observational longitudinal study design |
| Chanzo asilia≠ | Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260087840 | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Majina mbadala | panel causal-comparative design, longitudinal ex post facto research, panel ex post facto study, repeated-measures causal-comparative study | longitudinal study, follow-up study, panel study, incidence study |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | Panel-based causal-comparative research is a quantitative observational design that tracks the same sample of participants or units across multiple time points and then compares pre-existing groups to identify differences in outcomes. By combining the temporal depth of a panel structure with the group-contrast logic of causal-comparative (ex post facto) methodology, it allows researchers to examine how naturally occurring conditions — such as treatment exposure, policy changes, or demographic characteristics — relate to outcomes over time, without experimental random assignment. | 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. |
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