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Analysing Misleading Discrete Responses: A Logit Model Based on Misclassified Data

  • Steven B. Caudill
  • Franklin G. Mixon

This study presents an alternative to direct questioning and randomized response approaches to obtain survey information about sensitive issues. The approach used here is based on a logit model that can be used when survey data on the dependent variable are misclassified. The method is applied to a direct survey of undergraduate cheating behaviour. Student responses may not always be truthful. In particular, a student claiming to be a non-cheater may actually be a cheater. The results indicate that the incidence of cheating in our sample is approximately 70% rather than the self-reported value of 51%. Copyright 2005 Blackwell Publishing Ltd.

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Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 67 (2005)
Issue (Month): 1 (02)
Pages: 105-113

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Handle: RePEc:bla:obuest:v:67:y:2005:i:1:p:105-113
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  1. Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
  2. Toyoda, Toshihsa & Wallace, T D, 1976. "Optimal Critical Values for Pre-Testing in Regression," Econometrica, Econometric Society, vol. 44(2), pages 365-75, March.
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