Salīdzināt metodes

	Salīdzinošā paneļu izpēte	Longitudinālie pētījumi	Daudzlīmeņu modelēšana	Paneļu izpēte
Nozare	Pētījuma dizains	Pētījuma dizains	Pētniecības statistika	Pētījuma dizains
Saime	Process / pipeline	Process / pipeline	Process / pipeline	Process / pipeline
Izcelsmes gads	1970s–1980s (formal integration of comparative and panel designs)	Late 19th–early 20th century; methodologically codified through the 20th century	1992	1970s-1980s (econometric formalization); earlier social survey use from 1940s
Autors	Developed across social science disciplines; seminal formalizations by Cheng Hsiao (panel econometrics) and Melvin Kohn (comparative sociology)	No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett	Anthony Bryk and Stephen Raudenbush	Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s
Tips	Quantitative longitudinal comparative design	Quantitative (or mixed) observational research design	Method	Quantitative longitudinal observational design
Pirmavots	Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. ISBN: 978-1107038691	Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841	Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical Linear Models: Applications and Data Analysis Methods. SAGE Publications.	Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717
Citi nosaukumi	cross-national panel study, comparative longitudinal panel, pooled cross-sectional time-series design, multi-group panel design	longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study	HLM, mixed-effects models, random effects models, MLM	panel study, panel survey, longitudinal panel, repeated-measures panel
Saistītās	3	4	3	3
Kopsavilkums	Comparative panel research tracks the same individuals, organizations, or macro-level units (e.g., countries, regions) across multiple time points while simultaneously comparing findings across two or more distinct groups or contexts. By combining the temporal depth of panel measurement with the analytical leverage of systematic comparison, this design can distinguish change processes that are universal from those that are context-specific — a capability neither pure panel nor single-sample longitudinal designs offer on their own.	Longitudinal research is an observational design in which the same participants, groups, or units are measured repeatedly over an extended period. Rather than capturing a single snapshot, it tracks change, stability, and temporal sequencing of variables — making it the primary non-experimental strategy for studying development, growth, decline, and the unfolding of causal processes across time.	Multilevel modeling (also called hierarchical linear modeling, mixed-effects modeling) is a statistical framework for analyzing data organized in nested or clustered structures—students within schools, patients within hospitals, repeated measures within individuals. Developed by Bryk and Raudenbush (1992), it accounts for dependency among observations and partitions variance into levels (within-cluster and between-cluster), enabling valid inference and revealing context effects. Essential in education, medicine, organizational research, and any field where data have natural hierarchies.	Panel research is a quantitative longitudinal design in which the same individuals, organizations, or other units are measured repeatedly across two or more time points. Unlike cross-sectional surveys that capture a single snapshot, a panel tracks change within units, enabling researchers to separate genuine within-unit change from between-unit differences and to model causal dynamics over time.