An evaluation of k-nearest neighbour imputation using Likert data

@article{Jnsson2004AnEO,
  title={An evaluation of k-nearest neighbour imputation using Likert data},
  author={Per J{\"o}nsson and Claes Wohlin},
  journal={10th International Symposium on Software Metrics, 2004. Proceedings.},
  year={2004},
  pages={108-118}
}
Studies in many different fields of research suffer from the problem of missing data. With missing data, statistical tests will lose power, results may be biased, or analysis may not be feasible at all. There are several ways to handle the problem, for example through imputation. With imputation, missing values are replaced with estimated values according to an imputation method or model. In the k-nearest neighbour (k-NN) method, a case is imputed using values from the k most similar cases. In… CONTINUE READING
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