Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise Fenomenológica Interpretativa Comparativa× | Estudo de Caso Comparativo× | |
|---|---|---|
| Área | Qualitativo | Qualitativo |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1996 (IPA); comparative applications prominent from 2000s onward | 1984 (Yin); 1995 (Stake) |
| Autor original≠ | Jonathan A. Smith (IPA); comparative extension by IPA research community | Robert K. Yin; Robert E. Stake |
| Tipo≠ | Qualitative research design | Qualitative / mixed research design |
| Fonte seminal≠ | Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretative Phenomenological Analysis: Theory, Method and Research. Sage. ISBN: 978-1412908344 | Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage. ISBN: 978-1506336169 |
| Outros nomes | Comparative IPA, cross-group IPA, IPA comparative design, multi-group interpretative phenomenological analysis | cross-case study, multi-site case study, multiple case study design, comparative case analysis |
| Relacionados≠ | 5 | 4 |
| Resumo≠ | Comparative Interpretative Phenomenological Analysis (Comparative IPA) applies the IPA framework — developed by Jonathan A. Smith — to examine and contrast the lived experiences of two or more distinct groups or individuals. Rather than producing a single composite description, it preserves within-group detail and then performs a principled cross-group comparison, revealing how the same phenomenon is experienced differently depending on context, identity, or circumstance. | Comparative case study is a qualitative research design in which two or more bounded cases are studied in depth and then systematically compared to identify similarities, differences, and patterns across contexts. Rooted in Yin's replication logic and Stake's multiple case framework, it is particularly suited to questions that ask how or why a phenomenon unfolds differently — or similarly — across distinct settings, populations, or time periods. |
| ScholarGateConjunto de dados ↗ |
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