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| Q-Methodologie× | Faktorenanalyse× | Thematische Analyse× | |
|---|---|---|---|
| Fachgebiet≠ | Psychologie | Forschungsstatistik | Qualitative Forschung |
| Familie≠ | Hypothesis test | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1935 | 1931 | 2006 |
| Urheber≠ | William Stephenson | Louis Leon Thurstone | Virginia Braun and Victoria Clarke |
| Typ≠ | Q-sort ranking technique | Method | Method |
| Wegweisende Quelle≠ | Stephenson, W. (1935). Technique of factor analysis. Nature, 136(3434), 297. DOI ↗ | Thurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press. DOI ↗ | Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗ |
| Aliasnamen≠ | Q-Sort, Q-Technique | EFA, CFA, latent variable modeling | TA, Reflexive Thematic Analysis |
| Verwandt | 3 | 3 | 3 |
| Zusammenfassung≠ | Q-Methodology is a mixed-methods approach that combines quantitative factor analysis with qualitative interpretation to identify distinct perspectives, viewpoints, or 'factors' shared by groups of people. Introduced by William Stephenson in 1935, it uses Q-sorts—where participants rank statements on a continuum—to measure subjective viewpoints systematically. The method applies factor analysis to correlations among Q-sorts (not items), revealing common patterns of opinion or attitude that transcend individual differences. | Factor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data. | Thematic Analysis (TA) is a qualitative research methodology for identifying, analyzing, and reporting patterns (themes) in qualitative data. Developed systematically by Virginia Braun and Victoria Clarke (2006), TA is flexible and accessible, applicable across diverse theoretical frameworks and data types, making it one of the most widely used qualitative methods in psychology, health research, and social sciences. |
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