Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Ubunifu wa Utafiti wa Longitudinal Ex Post Facto× | Utafiti wa Kiuhusiano wa Kiwimbi× | |
|---|---|---|
| Nyanja | Muundo wa Utafiti | Muundo wa Utafiti |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1964–1986 (Kerlinger 1964 first edition; Campbell & Stanley 1966) | Mid-20th century (formalized 1940s–1960s) |
| Mwanzilishi≠ | 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.) |
| Aina≠ | Non-experimental quantitative research design | Non-experimental quantitative design |
| Chanzo asilia≠ | 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 |
| Majina mbadala | 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 |
| Zinazohusiana≠ | 5 | 3 |
| Muhtasari≠ | 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. |
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