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Tabulation of multiple responses

Author

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  • Ben Jann

    (Soziologie, ETH Zurich)

Abstract

Although multiple response questions are quite common in survey research, Stata's official release does not provide much possibility for an effective analysis of multiple response variables. For example, in a study on drug addiction an interview question might be: "Which substances did you consume during the last four weeks?" The respondents just list all the drugs they took if any, e.g., an answer could be "cannabis, cocaine, heroin" or "ecstasy, cannabis" or "none", etc. Usually, the responses to such questions are held as a set of variables and, therefore, cannot be easily tabulated. I will address this issue and present a new module to compute one- and two-way tables of multiple responses. The module supports several types of data structure, provides significance tests and offers various options to control the computation and display of the results.

Suggested Citation

  • Ben Jann, 2004. "Tabulation of multiple responses," United Kingdom Stata Users' Group Meetings 2004 12, Stata Users Group.
    • Handle: RePEc:boc:usug04:12
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    References listed on IDEAS

    as
    1. Nicholas J. Cox, 2004. "Speaking Stata: Graphing categorical and compositional data," Stata Journal, StataCorp LP, vol. 4(2), pages 190-213, June.
    2. Roger Newson, 2003. "Confidence intervals and p-values for delivery to the end user," Stata Journal, StataCorp LP, vol. 3(3), pages 245-269, September.
    3. Nicholas J. Cox & Ulrich Kohler, 2003. "Speaking Stata: On structure and shape: the case of multiple responses," Stata Journal, StataCorp LP, vol. 3(1), pages 81-99, March.
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    Cited by:

    1. Jessica Neicun & Justin Christopher Yang & Hueyjong Shih & Pranay Nadella & Robin van Kessel & Attilio Negri & Kasia Czabanowska & Carol Brayne & Andres Roman-Urrestarazu, 2020. "Lifetime prevalence of novel psychoactive substances use among adults in the USA: Sociodemographic, mental health and illicit drug use correlates. Evidence from a population-based survey 2007–2014," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-18, October.
    2. Lutz Bornmann & K. Brad Wray & Robin Haunschild, 2020. "Citation concept analysis (CCA): a new form of citation analysis revealing the usefulness of concepts for other researchers illustrated by exemplary case studies including classic books by Thomas S. K," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1051-1074, February.
    3. Bornmann, Lutz & Ozimek, Adam, 2012. "Stata commands for importing bibliometric data and processing author address information," Journal of Informetrics, Elsevier, vol. 6(4), pages 505-512.

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