Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Design de Métodos Mistos de Triangulação Concorrente× | Validade Convergente× | |
|---|---|---|
| Área≠ | Delineamento de pesquisa | Psicometria |
| Família≠ | Process / pipeline | Latent structure |
| Ano de origem≠ | 2007 (formally named in Creswell & Plano Clark, 1st ed.) | 1959 |
| Autor original≠ | John W. Creswell & Vicki L. Plano Clark | Donald T. Campbell & Donald W. Fiske |
| Tipo≠ | Mixed methods research design | Validity evidence / construct validation |
| Fonte seminal≠ | Creswell, J. W., & Plano Clark, V. L. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Sage. ISBN: 978-1412975179 | Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105. DOI ↗ |
| Outros nomes≠ | convergent parallel design, triangulation design, QUAN+QUAL concurrent design, simultaneous triangulation | convergent construct validity, convergence validity, AVE-based convergent validity |
| Relacionados≠ | 5 | 4 |
| Resumo≠ | The concurrent triangulation mixed methods design collects quantitative and qualitative data simultaneously, analyzes each strand independently, and then merges the results to assess whether the two data sources corroborate one another. Often called the convergent parallel design, it is one of the foundational configurations in mixed methods research and is chosen specifically when the researcher wants to cross-validate or triangulate findings from two distinct methodological traditions. | Convergent validity is the degree to which multiple indicators that are theoretically expected to measure the same construct actually correlate with one another. It is one of the two complementary forms of construct validity identified by Campbell and Fiske (1959) and is now routinely assessed via factor loadings and the Average Variance Extracted (AVE) statistic in SEM-based scale validation. |
| ScholarGateConjunto de dados ↗ |
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