Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Дизайн смешанных методов с одновременной триангуляцией× | Конвергентная валидность× | |
|---|---|---|
| Область≠ | Дизайн исследования | Психометрия |
| Семейство≠ | Process / pipeline | Latent structure |
| Год появления≠ | 2007 (formally named in Creswell & Plano Clark, 1st ed.) | 1959 |
| Автор метода≠ | John W. Creswell & Vicki L. Plano Clark | Donald T. Campbell & Donald W. Fiske |
| Тип≠ | Mixed methods research design | Validity evidence / construct validation |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия≠ | convergent parallel design, triangulation design, QUAN+QUAL concurrent design, simultaneous triangulation | convergent construct validity, convergence validity, AVE-based convergent validity |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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