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	Mixed Methods Research	Grounded Theory	Undersökningsforskning
Ämnesområde	Kvalitativa metoder	Kvalitativ forskning	Forskningsdesign
Familj	Process / pipeline	Process / pipeline	Process / pipeline
Ursprungsår	—	1967	Late 19th century; methodologically systematised 1940s–1960s
Upphovsperson	—	Barney Glaser and Anselm Strauss	Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s
Typ	Research design framework	Method	Quantitative (and mixed) non-experimental design
Ursprungskälla	Creswell, J.W. & Plano Clark, V.L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379	Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine.	Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000
Alias	Karma Yöntem Araştırması (Mixed Methods), multi-method research, triangulation design	GT, Grounded Theory Approach	survey methodology, questionnaire research, survey design, survey study
Närliggande	4	3	4
Sammanfattning	Mixed methods research is a systematic research design in which quantitative and qualitative data are collected and analysed within a single study. Formalised by Creswell and Plano Clark (2003, 3rd ed. 2018), it offers three principal design variants — concurrent, sequential, and transformative — and strengthens findings through triangulation across both data strands.	Grounded Theory (GT) is a systematic qualitative research methodology in which theory emerges directly from data through iterative analysis, rather than being imposed before data collection. Developed by Barney Glaser and Anselm Strauss in 1967, GT prioritizes generating explanatory frameworks grounded in evidence.	Survey research is a quantitative (and sometimes mixed-methods) design in which a researcher collects standardised self-report data from a sample drawn from a defined population, using a questionnaire or structured interview. It is the dominant non-experimental strategy for describing population characteristics, estimating prevalence, mapping attitude distributions, and testing bivariate or multivariate associations across social, behavioural, and health sciences.