Analysing Misleading Discrete Responses: A Logit Model Based on Misclassified Data*
提出一种替代直接提问和随机化回答的方法，利用Logit模型处理因变量误分类的调查数据，并应用于大学生作弊行为调查，发现实际作弊率约70%而非自报的51%。
Abstract 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%.