Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Сравнително напречно изследване× | Напречно-секторно изследване× | |
|---|---|---|
| Област | Дизайн на изследването | Дизайн на изследването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | Mid-20th century (widely formalized from 1950s onward) | Late 19th–early 20th century; methodologically codified through the 20th century |
| Създател≠ | Epidemiological tradition; formalized in observational study typologies | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Тип≠ | Observational quantitative design | Quantitative (or mixed) observational research design |
| Основополагащ източник≠ | Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195083507 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Други названия | comparative cross-sectional survey, cross-sectional comparative study, multi-group cross-sectional design, cross-sectional group comparison | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Свързани≠ | 3 | 4 |
| Резюме≠ | Comparative cross-sectional research is a quantitative observational design that measures and compares characteristics, attitudes, or outcomes across two or more pre-defined groups at a single point in time. By building the comparison into the sampling frame rather than treating it as a secondary analysis step, the design yields group-level contrasts without requiring follow-up measurement, making it efficient for describing between-group differences in prevalence, mean levels, or associations. | 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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