Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Salīdzinošais vairāku gadījumu pētījums× | Daudzpusīgā gadījumu izpēte× | |
|---|---|---|
| Nozare | Kvalitatīvās metodes | Kvalitatīvās metodes |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1984 (Yin); 2006 (Stake multiple-case analysis) | 1980s–1990s (Yin's first edition 1984; Stake's collective case study concept 1995) |
| Autors≠ | Robert K. Yin; Robert E. Stake | Robert K. Yin (systematic replication logic); Robert E. Stake (naturalistic/collective case tradition) |
| Tips≠ | Qualitative comparative research design | Qualitative research method |
| Pirmavots | Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage. ISBN: 978-1506336169 | Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage. ISBN: 978-1506336169 |
| Citi nosaukumi | multi-site case study, cross-case analysis, comparative case research, multi-case comparative design | comparative case study, multi-site case study, collective case study, cross-case analysis |
| Saistītās≠ | 5 | 6 |
| Kopsavilkums≠ | Comparative multiple case study is a qualitative research design in which two or more bounded cases are studied in depth and then systematically compared to identify patterns, contrasts, and transferable findings. Rooted in Robert Yin's case study methodology and Robert Stake's multiple-case analysis framework, it combines the rich contextual insight of single-case work with the analytical leverage gained by examining how phenomena unfold similarly or differently across distinct settings. | Multiple-case study design investigates two or more bounded real-world cases using the same research protocol, then compares findings across cases to identify patterns, contrasts, and explanatory insights that a single case could not produce. Developed primarily through Robert Yin's replication logic and Robert Stake's collective case tradition, the approach is particularly powerful when a researcher needs to determine whether a phenomenon occurs under varied conditions or to test an emerging theoretical explanation against rival contexts. |
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