方法对比

	混合方法研究	扎根理论	调查研究
领域	质性	质性研究	研究设计
方法族	Process / pipeline	Process / pipeline	Process / pipeline
起源年份	—	1967	Late 19th century; methodologically systematised 1940s–1960s
提出者	—	Barney Glaser and Anselm Strauss	Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s
类型	Research design framework	Method	Quantitative (and mixed) non-experimental design
开创性文献	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
别名	Karma Yöntem Araştırması (Mixed Methods), multi-method research, triangulation design	GT, Grounded Theory Approach	survey methodology, questionnaire research, survey design, survey study
相关	4	3	4
摘要	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.