विधियों की तुलना करें

	पैनल-आधारित कार्य-कारण तुलनात्मक अनुसंधान	अनुदैर्ध्य अनुसंधान
क्षेत्र	अनुसंधान अभिकल्प	अनुसंधान अभिकल्प
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	1950s–1980s (formalized across educational and social science methodology literature)	Late 19th–early 20th century; methodologically codified through the 20th century
प्रवर्तक	Building on causal-comparative tradition (John W. Best, 1959) extended to panel data structures in social and educational research	No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett
प्रकार	Quantitative observational research design	Quantitative (or mixed) observational research design
मौलिक स्रोत	Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260087840	Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841
उपनाम	panel causal-comparative design, longitudinal ex post facto research, panel ex post facto study, repeated-measures causal-comparative study	longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study
संबंधित	5	4
सारांश	Panel-based causal-comparative research is a quantitative observational design that tracks the same sample of participants or units across multiple time points and then compares pre-existing groups to identify differences in outcomes. By combining the temporal depth of a panel structure with the group-contrast logic of causal-comparative (ex post facto) methodology, it allows researchers to examine how naturally occurring conditions — such as treatment exposure, policy changes, or demographic characteristics — relate to outcomes over time, without experimental random assignment.	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.