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Chattoe-Brown, Edmund – International Journal of Social Research Methodology, 2021
This article demonstrates how a technique called Agent-Based Modelling can address a significant challenge for effective interdisciplinarity. Different disciplines and research methods make divergent assertions about what a satisfactory explanation requires. However, without a unified framework analysing the implications of these differences…
Descriptors: Interdisciplinary Approach, Models, Research Methodology, Statistical Analysis
Cooper, Barry; Glaesser, Judith – International Journal of Social Research Methodology, 2016
Ragin's Qualitative Comparative Analysis (QCA) is often used with small to medium samples where the researcher has good case knowledge. Employing it to analyse large survey datasets, without in-depth case knowledge, raises new challenges. We present ways of addressing these challenges. We first report a single QCA result from a configurational…
Descriptors: Social Science Research, Robustness (Statistics), Educational Sociology, Comparative Analysis
Pohl, Steffi; Steiner, Peter M.; Eisermann, Jens; Soellner, Renate; Cook, Thomas D. – Educational Evaluation and Policy Analysis, 2009
Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…
Descriptors: Statistical Analysis, Social Science Research, Statistical Bias, Statistical Inference

Draper, David – Journal of Educational and Behavioral Statistics, 1995
The use of hierarchical models in social science research is discussed, with emphasis on causal inference and consideration of the limitations of hierarchical models. The increased use of Gibbs sampling and other Markov-chain Monte Carlo methods in the application of hierarchical models is recommended. (SLD)
Descriptors: Causal Models, Comparative Analysis, Markov Processes, Maximum Likelihood Statistics