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The strategic choice of a data collection methodology is the most critical determinant of a study's validity and generalizability in social and behavioral research. This paper synthesizes the methodological literature, critically comparing Surveys, In-depth Interviews, Structured Observation, and Controlled Experiments across five key dimensions: External Validity (Generalizability), Internal Validity (Causality/Richness), Cost, Time-to-Completion, and Vulnerability to Bias. The findings confirm that an inherent methodological trade-off exists: methods designed for breadth and efficiency (Surveys) sacrifice contextual richness, while methods prioritizing depth and authenticity (Interviews/Observation) are resource-intensive and often struggle with external validity. Crucially, only the Controlled Experiment is validated for establishing causal inference due to its manipulation and randomization capabilities. The analysis culminates in a framework advocating for methodological triangulation (mixed-methods) as the most effective strategy to mitigate the intrinsic limitations of any single approach, thereby enhancing the overall robustness of empirical social science research.
Keywords:
Data analysis Techniques, Survey, Modelling
Cite Article:
"A Comparative Analysis of Data Collection Methodologies: Trade-offs in Validity, Cost, and Richness for Empirical Social Science", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 10, page no.a689-a692, October-2025, Available :http://www.ijrti.org/papers/IJRTI2510069.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator