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Implications of errors in survey data: a Bayesian model

Author: Gaba, Anil ; Winkler, Robert L.INSEAD Area: Technology and Operations ManagementIn: Management Science, vol. 38, no. 7, jul. 1992 Language: EnglishDescription: p. 913-925.Type of document: INSEAD ArticleNote: Please ask the Library for this articleAbstract: Data from surveys often include errors, and such errors can have a serious effect on inferences about behaviour or perceptions. In this paper a model is developed for making inferences based on dichotomous survey data with possible errors. A likelihood analysis reveals an identification problem, which can be avoided when a Bayesian approach is taken. The model is illustrated with purchase recall data from two previous studies, and the analysis shows that errors can have a significant impact on inferences about behaviour. Ignoring such errors leads to point estimates that are unreallistically narrow. The effective amount of information in the survey data is reduced dramatically by the presence of errors. These results have important implications for the use and value of survey data in marketing and in many other areas
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Data from surveys often include errors, and such errors can have a serious effect on inferences about behaviour or perceptions. In this paper a model is developed for making inferences based on dichotomous survey data with possible errors. A likelihood analysis reveals an identification problem, which can be avoided when a Bayesian approach is taken. The model is illustrated with purchase recall data from two previous studies, and the analysis shows that errors can have a significant impact on inferences about behaviour. Ignoring such errors leads to point estimates that are unreallistically narrow. The effective amount of information in the survey data is reduced dramatically by the presence of errors. These results have important implications for the use and value of survey data in marketing and in many other areas

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