Testing the adequacy of varying coefficient models with missing responses at random

Wangli Xu*, Lixing ZHU

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

In this paper, we investigate checking the adequacy of varying coefficient models with response missing at random. In doing so, we first construct two completed data sets based on imputation and marginal inverse probability weighted methods, respectively. The empirical process-based tests by using these two completed data sets are suggested and the asymptotic properties of the test statistics under the null and local alternative hypotheses are studied. Because the limiting null distribution is intractable, a Monte Carlo approach is applied to approximate the distribution to determine critical values. Simulation studies are carried out to examine the performance of our method, and a real data set from an environmental study is analyzed for illustration.

Original languageEnglish
Pages (from-to)53-69
Number of pages17
JournalMetrika
Volume76
Issue number1
DOIs
Publication statusPublished - Jan 2013

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Empirical process
  • Imputation
  • Model checking
  • Response missing at random
  • Varying coefficient models

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