विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| अनुदैर्ध्य संबंधात्मक सर्वेक्षण× | अनुदैर्ध्य अनुसंधान× | |
|---|---|---|
| क्षेत्र | अनुसंधान अभिकल्प | अनुसंधान अभिकल्प |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1960s–1980s (formalized in panel and longitudinal survey literature) | Late 19th–early 20th century; methodologically codified through the 20th century |
| प्रवर्तक≠ | Classical survey methodology (Campbell & Stanley, 1963; Kessler & Greenberg, 1981) | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| प्रकार≠ | Non-experimental quantitative design | Quantitative (or mixed) observational research design |
| मौलिक स्रोत≠ | Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press. ISBN: 978-0195152968 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| उपनाम | longitudinal correlational survey, prospective relational survey, repeated-measures relational survey, panel relational survey | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| संबंधित≠ | 3 | 4 |
| सारांश≠ | A longitudinal relational survey follows the same sample at two or more time points, collecting structured questionnaire data each wave and examining how the relationships among variables change, strengthen, weaken, or emerge across time. Unlike a cross-sectional relational survey that offers a single snapshot, this design captures temporal dynamics and allows researchers to test whether earlier measurements predict later outcomes, making it valuable for studying development, attitude change, and causal ordering. | 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. |
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