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	Hierarchical Survey Research	सर्वेक्षण अनुसंधान
क्षेत्र	अनुसंधान अभिकल्प	अनुसंधान अभिकल्प
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	1986–1992 (formalization of multilevel methods for nested survey data)	Late 19th century; methodologically systematised 1940s–1960s
प्रवर्तक	Developed through contributions of Aitkin, Longford, Goldstein, Bryk, and Raudenbush in the 1980s–1990s	Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s
प्रकार	Quantitative survey design with multilevel analysis	Quantitative (and mixed) non-experimental design
मौलिक स्रोत	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
उपनाम	multilevel survey research, nested survey design, multilevel survey design, HLM-based survey research	survey methodology, questionnaire research, survey design, survey study
संबंधित	6	4
सारांश	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.	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.