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An Item Response Model for Understanding Item Non-response in Ghanaian Surveys

机译:理解加纳调查中项目未答复的项目响应模型

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Survey research has been widely used in public opinion research in Ghana. Ghanaian researchers are happy about data richness and they are also concerned about data quality. In this paper Item Response Theory (IRT) has been used to identify the most appropriate IRT model for understanding item. The techniques are appropriate and practical. A questionnaire data on Ghana collected in the 5th wave of the World Values Survey was used for the analysis. The five categories of survey questions that are most difficult to answer by respondents were Life Related Questions, Value Related Questions, Political Related Questions, Income Related Questions and Democracy Related Questions. Missing or ‘don’t know’ responses were assigned a 0 score, and 1 was assigned to answered items. The data was analysed based on four IRT models namely, the constrained Rasch model, the unconstrained Rasch model, the two parameter logistic model, and the three parameter logistic model. These models were explored to determine the most appropriate model for the data. In this paper, the unconstrained Rasch model emerged as the best model for understanding item non-response. We found that, income related questions had the highest difficulty parameter, hence the most difficult category of survey questions to answer. It was also found that, if an individual does not answer a survey question or give a ‘don’t know’ answer, it is not only because of the question’s difficulty but also because the respondent doesn’t want to answer.
机译:调查研究已在加纳的舆论研究中广泛使用。加纳的研究人员对数据丰富性感到高兴,并且也对数据质量感到担忧。在本文中,项目响应理论(IRT)已用于识别最合适的IRT模型以理解项目。该技术是适当和实用的。分析使用了在第五次世界价值调查中收集的关于加纳的调查表数据。受访者最难以回答的五种调查问题是与生活有关的问题,与价值有关的问题,与政治有关的问题,与收入有关的问题和与民主有关的问题。缺失或“不知道”的答案被分配为0分,已回答的项目被分配为1分。基于约束的Rasch模型,无约束的Rasch模型,两参数对数模型和三参数对数模型四个IRT模型对数据进行了分析。探索了这些模型以确定最合适的数据模型。在本文中,无约束的Rasch模型成为理解项目无响应的最佳模型。我们发现,与收入相关的问题具有最高的难度参数,因此最难回答的调查问题类别。还发现,如果某人不回答调查问题或给出“不知道”答案,那不仅是因为问题的难度,还因为受访者不想回答。

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