Double sampling designs in multivariate linear models with missing variables

Noam Cohen, Ori Davidov, Yoel Haitovsky

Research output: Contribution to journalArticlepeer-review


We provide a method for finding the optimal double sampling plan for estimating the mean value of a continuous outcome. It is assumed that the fallible and true outcome data are related by a multivariate linear regression model where only some of the explanatory variables are sampled. Conditions under which double sampling is preferred over standard sampling plans are determined. An application of the method to a well-known data set on air pollution is presented.

Original languageEnglish
Pages (from-to)1156-1166
Number of pages11
JournalCommunications in Statistics Part B: Simulation and Computation
Issue number6
StatePublished - Jun 2008


  • Double sampling
  • Missing variables
  • Optimal design

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation


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