The additive model affected by missing completely at random in the covariate
type: Item
instance of: scholarly article
title: The additive model affected by missing completely at random in the covariate
zbMATH Open document ID: 1063.62055
DOI: 10.1007/BF02892060
author: Thomas Nittner
published in: Computational Statistics
publication date: 2005-05-20T00:00:00Z
review text: This paper focuses on a comparison of several imputation procedures within the simple additive model \(y=f(x)+\varepsilon\), where the independent variable \(x\) is affected by missing completely randomly. Such imputation methods as complete case analysis, mean imputation plus random noise, single imputation and two kinds of nearest neighbour imputations are investigated and compared within a simulation experiment based on the sample mean squared error, estimated variances and sample bias of the estimates of \(f(x)\) at the knots.
Mathematics Subject Classification ID: 62G08
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 65D10
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 2169409
zbMATH Keywords: missing data
zbMATH Keywords: imputation methods
zbMATH Keywords: additive model
zbMATH Keywords: complete case analysis
zbMATH Keywords: stochastic mean imputation
zbMATH Keywords: nearest neighbour imputation
describes a project that uses: Fahrmeir
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 2169409