ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Кросс-секционное каузально-сравнительное исследование×Лонгитюдное каузально-сравнительное исследование×
ОбластьДизайн исследованияДизайн исследования
СемействоProcess / pipelineProcess / pipeline
Год появления1960s onward1970s–1980s (as an established combined design in educational and social research)
Автор методаDonald T. Campbell and Julian C. Stanley (quasi-experimental foundations); refined in education research by various methodologistsSynthesized from causal-comparative tradition (Kerlinger, 1973) and longitudinal design frameworks (Goldstein, 1979)
ТипNon-experimental quantitative designNon-experimental quantitative research design
Основополагающий источникFrankfort-Nachmias, C., & Nachmias, D. (2015). Research Methods in the Social Sciences (8th ed.). Worth Publishers. ISBN: 978-1429295154Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2009). How to Design and Evaluate Research in Education (7th ed.). McGraw-Hill. ISBN: 978-0073525532
Другие названияcross-sectional ex post facto design, single-wave causal-comparative study, cross-sectional group-comparison design, cross-sectional criterion-group studylongitudinal ex post facto design, longitudinal causal-comparative design, repeated-measures causal-comparative research, prospective causal-comparative study
Связанные34
СводкаCross-sectional causal-comparative research compares two or more pre-existing groups — defined by a characteristic or experience that has already occurred — on one or more outcome variables, with all data collected at a single point in time. Because the presumed cause (group membership) precedes measurement but cannot be manipulated, the design sits between purely descriptive and truly experimental work. It is widely used in education, psychology, and social sciences when randomization is impossible or unethical.Longitudinal causal-comparative research is a non-experimental quantitative design that compares pre-existing groups on one or more dependent variables across multiple measurement points over time. Unlike true experiments, the researcher does not manipulate the independent variable; instead, naturally occurring group differences (e.g., gender, socioeconomic status, diagnostic category) are examined to explore their relationship to outcomes as they evolve longitudinally.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: Cross-sectional causal-comparative research · Longitudinal Causal-Comparative Research. Получено 2026-06-19 из https://scholargate.app/ru/compare