A goodness-of-fit test for a varying-coefficients model in longitudinal studies

Wang Li Xu*, Lixing ZHU

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

5 Citations (Scopus)


In this paper, we construct an empirical process-based test to examine the adequacy of a varying-coefficient model. A Monte Carlo approach is applied to approximate the null distribution of the test. Beyond the desired features that are shared by the existing empirical process-based tests, the Monte Carlo approximation makes the test self-invariant such that studentisation for the test statistic is not needed. Thus, the variance of residuals, as a studentising constant that is model dependent and may deteriorate the power of test, is no need to estimate. Simulations and an example are provided to illustrate our methodology.

Original languageEnglish
Pages (from-to)427-440
Number of pages14
JournalJournal of Nonparametric Statistics
Issue number4
Publication statusPublished - May 2009

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Empirical process
  • Monte Carlo approximation
  • Varying-coefficient longitudinal model


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