Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Διαχρονικός Σχεδιασμός Ex Post Facto× | Έρευνα Επιμήκους Τροχιάς× | |
|---|---|---|
| Πεδίο | Ερευνητικός Σχεδιασμός | Ερευνητικός Σχεδιασμός |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 1964–1986 (Kerlinger 1964 first edition; Campbell & Stanley 1966) | Late 19th–early 20th century; methodologically codified through the 20th century |
| Δημιουργός≠ | Fred N. Kerlinger (systematized); Donald T. Campbell & Julian C. Stanley (quasi-experimental framework) | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Τύπος≠ | Non-experimental quantitative research design | Quantitative (or mixed) observational research design |
| Θεμελιώδης πηγή≠ | Kerlinger, F. N. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417498 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Εναλλακτικές ονομασίες | longitudinal causal-comparative design, longitudinal after-the-fact design, longitudinal retrospective design, LEPF design | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Συναφείς≠ | 5 | 4 |
| Σύνοψη≠ | 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 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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