Applying Multiple Imputation with Geostatistical Models to Account for Item Nonresponse in Environmental Data

被引：7
|
作者：
Munoz, Breda [1 ]
Lesser, Virginia M. [2 ,3 ]
Smith, Ruben A. [4 ]
机构：
[1] RTI Int, RTP, Durham, NC 27709 USA
[2] Oregon State Univ, Survey Res Ctr, Corvallis, OR 97331 USA
[3] Oregon State Univ, Stat, Corvallis, OR 97331 USA
[4] Oregon State Univ, Corvallis, OR 97331 USA
来源：
JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2010年 / 9卷 / 01期
关键词：
Environmental surveys; missing data; nonresponse;
D O I：
10.22237/jmasm/1272687960
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Methods proposed to solve the missing data problem in estimation procedures should consider the type of missing data, the missing data mechanism, the sampling design and the availability of auxiliary variables correlated with the process of interest. This article explores the use of geostatistical models with multiple imputation to deal with missing data in environmental surveys. The method is applied to the analysis of data generated from a probability survey to estimate Coho salmon abundance in streams located in western Oregon watersheds.
引用
收藏
页码：274 / 286
页数：13
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