Salīdzināt metodes

	Hierarhiskā aptaujas pētniecība	Longitudinālie aptauju pētījumi
Nozare	Pētījuma dizains	Pētījuma dizains
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1986–1992 (formalization of multilevel methods for nested survey data)	Mid-20th century (formalized ~1950s–1970s)
Autors	Developed through contributions of Aitkin, Longford, Goldstein, Bryk, and Raudenbush in the 1980s–1990s	Survey methodology tradition; codified in social sciences by scholars including W.S. Robinson (1950) and later Scott Menard
Tips	Quantitative survey design with multilevel analysis	Quantitative observational research design
Pirmavots	Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). Sage. ISBN: 978-1849202015	Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922452
Citi nosaukumi	multilevel survey research, nested survey design, multilevel survey design, HLM-based survey research	longitudinal survey study, repeated-measures survey, prospective survey design, panel survey
Saistītās	6	5
Kopsavilkums	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.	Longitudinal survey research collects structured questionnaire data from the same individuals (or units) at two or more points in time. Unlike a one-shot cross-sectional survey, this design captures change, stability, and temporal ordering of variables — enabling researchers to track trajectories, test causal sequences, and distinguish cohort effects from aging effects within a quantitative framework.