Methods are presented for analyzing data generated by asking respondents to rank a set of items. Based on a conditional logit model, these methods allow us to estimate and test for differences among items in respondents' preferences for them; to test for differences in item preferences across subpopulations; and to incorporate predictor variables describing respondents, items, or both. The models can be easily estimated with programs for proportional hazards models, and they can be generalized to allow for ties in the rankings. Detailed examples are given.
Sociological Methodology (SM) is the only American Sociological Association periodical publication devoted entirely to research methods. It is a compendium of new and sometimes controversial advances in social science methodology. Contributions come from diverse areas and have something new and useful--and sometimes surprising--to say about a wide range of methodological topics. SM seeks qualitative and quantitative contributions that address the full range of methodological problems confronted by empirical research in the social sciences, including conceptualization, data analysis, data collection, measurement, modeling, and research design. The journal provides a forum for engaging the philosophical issues that underpin sociological research. Papers published in SM are original methodological contributions, including new methodological developments, reviews or illustrations of recent developments that provide new methodological insights, and critical evaluative discussions of research practices and traditions. SM encourages the inclusion of applications to real-world sociological data. SM is published annually as an edited, hardbound book.
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Sociological Methodology
© 1994 American Sociological Association
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