Power-linear models for incomplete contingency tables with nonignorable non-responses |
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Authors: | Seongyoung Kim |
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Institution: | Institute of Economic Research, Korea University, Seoul, Korea |
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Abstract: | For categorical data exhibiting nonignorable non-responses, it is well known that maximum likelihood (ML) estimates with a boundary solution are implausible and do not provide a perfect fit to the observed data even for saturated models. We provide the conditions under which ML estimates for the generalized linear model (GLM) with the usual log/logit link function have a boundary solution. These conditions introduce a new GLM with appropriately defined power link functions where its ML estimates resolve the problems arising from a boundary solution and offer useful statistics for identifying the non-response mechanism. This model is applied to a real dataset and compared with Bayesian models. |
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Keywords: | boundary solution correlation generalized linear model nonignorable non-responses power link functions |
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