An introduction to missing data in statistical applications is given in the beginning. The main part of the book deals with selection models for nonignorable missing data. The theory of selection models is described and illustrated by examples. Maximum Likelihood as well as Bayesian estimation approaches are discussed. A selection model with a nonparametric missing model that allows to treat flexible missing patterns is developed. This approach is unique in literature. The proposed model is extended to a model for ...
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An introduction to missing data in statistical applications is given in the beginning. The main part of the book deals with selection models for nonignorable missing data. The theory of selection models is described and illustrated by examples. Maximum Likelihood as well as Bayesian estimation approaches are discussed. A selection model with a nonparametric missing model that allows to treat flexible missing patterns is developed. This approach is unique in literature. The proposed model is extended to a model for longitudinal data.
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Add this copy of Selection Models for Nonignorable Missing Data to cart. $84.53, good condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Hialeah, FL, UNITED STATES, published 2005 by Peter Lang GmbH, International.
Edition:
2005, Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften
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