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Analysing Survey Data With Incomplete Responses By Using A Method Based On Empirical Likelihood, Denis H. Y. Leung, Jing Qin
Analysing Survey Data With Incomplete Responses By Using A Method Based On Empirical Likelihood, Denis H. Y. Leung, Jing Qin
Research Collection School Of Economics
In many surveys, missing response is a common problem. As an example, Zahner, Jacobs, Freeman and Trainor analysed data from a study of child psychopathology in the State of Connecticut, USA. In that study, the response variable, psychopathology, was inferred from questions that were addressed to teachers of the children and was subject to a high level of missingness. However, the missing responses were supplemented by surrogate information that was provided by the parents and/or the primary care providers of the children. In such a situation, it is conceivable that the supplemental information can be used to recover some of …
Semi-Parametric Inference In A Bivariate (Multivariate) Mixture Model, Denis H. Y. Leung, Jing Qin
Semi-Parametric Inference In A Bivariate (Multivariate) Mixture Model, Denis H. Y. Leung, Jing Qin
Research Collection School Of Economics
We consider estimation in a bivariate mixture model in which the component distributions can be decomposed into identical distributions. Previous approaches to estimation involve parametrizing the distributions. In this paper, we use a semi-parametric approach. The method is based on the exponential tilt model of Anderson (1979), where the log ratio of probability (density) functions from the bivariate components is linear in the observations. The proposed model does not require training samples, i.e., data with confirmed component membership. We show that in bivariate mixture models, parameters are identifiable. This is in contrast to previous works, where parameters are identifiable if …