قارن الطرق

	تصميم دراسة طولية بأثر رجعي	البحث الارتباطي الطولي
المجال	تصميم البحث	تصميم البحث
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	1964–1986 (Kerlinger 1964 first edition; Campbell & Stanley 1966)	Mid-20th century (formalized 1940s–1960s)
صاحب الطريقة	Fred N. Kerlinger (systematized); Donald T. Campbell & Julian C. Stanley (quasi-experimental framework)	Rooted in early correlational methodology (Galton, Pearson late 19th c.); longitudinal extension formalized through panel studies in social sciences (mid-20th c.)
النوع	Non-experimental quantitative research design	Non-experimental quantitative design
المصدر التأسيسي	Kerlinger, F. N. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417498	Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2009). How to Design and Evaluate Research in Education (8th ed.). McGraw-Hill. ISBN: 978-0078097898
الأسماء البديلة	longitudinal causal-comparative design, longitudinal after-the-fact design, longitudinal retrospective design, LEPF design	longitudinal correlational study, prospective correlational design, longitudinal associational research, repeated-measures correlational design
ذات صلة	5	3
الملخص	A longitudinal ex post facto design combines the time-depth of longitudinal research with the retrospective logic of ex post facto inquiry. Participants are grouped by a naturally occurring characteristic or past event — not randomly assigned — and then observed or measured at multiple points over time. The goal is to trace how pre-existing differences between groups unfold or predict outcomes across an extended period, without the researcher ever manipulating the independent variable.	Longitudinal correlational research is a non-experimental quantitative design that examines the strength and direction of relationships among variables by collecting data from the same participants at two or more points in time. Unlike a cross-sectional correlational study, the longitudinal approach captures how associations evolve, persist, or dissolve across time, providing a stronger empirical basis for causal inference without experimental manipulation.