方法对比
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| 层级调查研究× | Comparative Survey Research× | |
|---|---|---|
| 领域 | 研究设计 | 研究设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1986–1992 (formalization of multilevel methods for nested survey data) | Mid-20th century onward |
| 提出者≠ | Developed through contributions of Aitkin, Longford, Goldstein, Bryk, and Raudenbush in the 1980s–1990s | Rooted in survey methodology traditions (Gallup, Likert, Lazarsfeld mid-20th century); comparative extension codified in social science research methods literature |
| 类型≠ | Quantitative survey design with multilevel analysis | Quantitative non-experimental research design |
| 开创性文献≠ | Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). Sage. ISBN: 978-1849202015 | Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000 |
| 别名 | multilevel survey research, nested survey design, multilevel survey design, HLM-based survey research | comparative survey design, cross-group survey, multi-group survey research, comparative questionnaire study |
| 相关≠ | 6 | 4 |
| 摘要≠ | Hierarchical survey research is a quantitative design that collects survey data from respondents who are naturally nested within higher-level units — such as students within classrooms, employees within organizations, or patients within hospitals — and uses multilevel (hierarchical linear) modeling to analyze variation at each level simultaneously. It is the standard approach whenever survey data have a clustered structure that would violate the independence assumption of ordinary regression. | Comparative survey research is a quantitative non-experimental design that systematically collects structured survey data from two or more clearly defined groups, populations, or contexts in order to identify, describe, and analyze similarities and differences among them. It extends basic survey research by making comparison the explicit organizing logic: rather than characterizing a single population, the goal is to detect how attitudes, behaviors, or outcomes vary across groups defined by nationality, culture, profession, demographic category, or time period. |
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