Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Vergelijkend dwarsdoorsnede-onderzoek× | Onderzoeksopzet× | |
|---|---|---|
| Vakgebied | Onderzoeksontwerp | Onderzoeksontwerp |
| Familie | Process / pipeline | Process / pipeline |
| Jaar van ontstaan≠ | Mid-20th century (widely formalized from 1950s onward) | Late 19th century; methodologically systematised 1940s–1960s |
| Grondlegger≠ | Epidemiological tradition; formalized in observational study typologies | Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s |
| Type≠ | Observational quantitative design | Quantitative (and mixed) non-experimental design |
| Oorspronkelijke bron≠ | 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 | Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000 |
| Aliassen | comparative cross-sectional survey, cross-sectional comparative study, multi-group cross-sectional design, cross-sectional group comparison | survey methodology, questionnaire research, survey design, survey study |
| Verwant≠ | 3 | 4 |
| Samenvatting≠ | 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. | 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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