Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Панельные обследования× | Исследование методом поперечных опросов× | |
|---|---|---|
| Область | Дизайн исследования | Дизайн исследования |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | Mid-20th century; formalized as a distinct design by the 1940s–1960s in sociological and economic research | 1930s–1950s (formalized with large-scale opinion and health surveys) |
| Автор метода≠ | Established through social science survey methodology; foundational reference: Kasprzyk et al. (1989) | Established through the social survey tradition (Bowley, Gallup, and others in the early-to-mid 20th century) |
| Тип≠ | Quantitative longitudinal observational design | Quantitative non-experimental design |
| Основополагающий источник≠ | Kasprzyk, D., Duncan, G., Kalton, G., & Singh, M. P. (Eds.). (1989). Panel Surveys. Wiley. ISBN: 978-0471617143 | Fowler, F. J. (2009). Survey Research Methods (4th ed.). Sage Publications. ISBN: 978-1412958929 |
| Другие названия | panel survey, longitudinal survey panel, repeated survey design, panel data survey | cross-sectional survey, single-occasion survey, prevalence survey design, snapshot survey |
| Связанные≠ | 5 | 4 |
| Сводка≠ | Panel-based survey research is a quantitative longitudinal design in which the same set of respondents — the panel — is surveyed with structured questionnaires at two or more distinct time points. By tracking the same individuals over time, the design captures intra-individual change, documents how outcomes evolve, and enables stronger causal inference than a single cross-sectional survey can provide. It is widely used in social science, economics, public health, and education research. | Cross-sectional survey research administers a structured questionnaire or interview to a representative sample of a population at one point in time. It is the workhorse design for estimating prevalence, describing group characteristics, and mapping associations among variables across a wide range of disciplines — from public health and education to marketing and political science. |
| ScholarGateНабор данных ↗ |
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