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Improving the Measurement of Shared Cultural Schemas with Correlational Class Analysis: Theory and Method

Andrei Boutyline

Sociological Science, May 29, 2017
DOI 10.15195/v4.a15

Measurement of shared cultural schemas is a central methodological challenge for the sociology of culture. Relational Class Analysis (RCA) is a recently developed technique for identifying such schemas in survey data. However, existing work lacks a clear definition of such schemas, which leaves RCA’s accuracy largely unknown. Here, I build on the theoretical intuitions behind RCA to arrive at this definition. I demonstrate that shared schemas should result in linear dependencies between survey rows—the relationship usually measured with Pearson’s correlation. I thus modify RCA into a “Correlational Class Analysis” (CCA). When I compare the methods using a broad set of simulations, results show that CCA is reliably more accurate at detecting shared schemas than RCA, even in scenarios that substantially violate CCA’s assumptions. I find no evidence of theoretical settings where RCA is more accurate. I then revisit a previous RCA analysis of the 1993 General Social Survey musical tastes module. Whereas RCA partitioned these data into three schematic classes, CCA partitions them into four. I compare these results with a multiple-groups analysis in structural equation modeling and find that CCA’s partition yields greatly improved model fit over RCA. I conclude with a parsimonious framework for future work.

Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.
Andrei Boutyline: Department of Sociology, University of California, Berkeley
Email: boutyline@berkeley.edu

Acknowledgements: This research was supported in part by fellowships from National Science Foundation Graduate Research Fellowship Program and Interdisciplinary Graduate Education and Research Traineeship Program. I thank Ronald Breiger, Neil Fligstein, John Flournoy, Amir Goldberg, Monica Lee, Valden Kamph, James Kitts, Fabiana Silva, Matthew Stimpson, Stephen Vaisey, Robb Willer, and the participants of the Berkeley Mathematical, Analytical, and Experimental Sociology workshop for feedback on the article. I am also grateful to Amir Goldberg for generously discussing RCA and making its software implementation available online. Direct all correspondence to Andrei Boutyline at Department of Sociology, 410 Barrows Hall, University of California, Berkeley, CA 94720. E-mail: boutyline@berkeley.edu

  • Citation: Boutyline, Andrei. 2017. “Improving the Measurement of Shared Cultural Schemas with Correlational Class Analysis: Theory and Method.” Sociological Science 4: 353-393.
  • Received: July 22, 2016
  • Accepted: April 4, 2017
  • Editors: Olav Sorenson, Gabriel Rossman
  • DOI: 10.15195/v4.a15