Conditional likelihood estimation and efficiency comparisons in proportional odds model with missing covariates

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题名:	Conditional likelihood estimation and efficiency comparisons in proportional odds model with missing covariates
作者:	Hsieh, S.H.a, Lee, S.M.a , Shen, P.S.b, Liu, M.F.
贡献者:	Department of Statistics, Tunghai University Taichung
关键词:	Conditional likelihood;Missing value;Ordinal categorical data;Proportional odds model
日期:	2011
上传时间:	2013-05-15T09:07:25Z (UTC)
摘要:	In this article, a conditional likelihood approach is developed for dealing with ordinal data with missing covariates in proportional odds model. Based on the validation data set, we propose the Breslow and Cain (Biometrika 75:11-20, 1988) type estimators using different estimates of the selection probabilities, which may be treated as nuisance parameters. Under the assumption that the observed covariates and surrogate variables are categorical, we present large sample theory for the proposed estimators and show that they are more efficient than the estimator using the true selection probabilities. Simulation results support the theoretical analysis. We also illustrate the approaches using data from a survey of cable TV satisfaction. ? The Institute of Statistical Mathematics, Tokyo 2009.
關聯:	Annals of the Institute of Statistical Mathematics Volume 63, Issue 5, October 2011, Pages 887-921
显示于类别:	[統計學系所] 期刊論文

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