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Related Experiment Videos

Testing for trend with count data

E A Weller1, L M Ryan

  • 1Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. eaw@biostat.harvard.edu

Biometrics
|June 18, 1998
PubMed
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For toxicological studies, the Jonckheere-Terpstra test and Poisson tests are compared for detecting dose-related trends. Recommendations guide test selection based on data dispersion and dose spacing for accurate trend detection.

Area of Science:

  • Toxicology
  • Biostatistics
  • Statistical Modeling

Background:

  • Detecting dose-related trends in toxicological count data is crucial for risk assessment.
  • Nonparametric (Jonckheere-Terpstra) and likelihood-based (Poisson) tests are commonly used but can yield conflicting results.
  • Conflicting conclusions from these tests necessitate a comparison of their performance under various conditions.

Purpose of the Study:

  • To compare the performance of the Jonckheere-Terpstra test and Poisson-based tests (including robust and conditional versions) for detecting dose-related trends.
  • To identify optimal test selection criteria based on data characteristics like overdispersion and discreteness.
  • To evaluate the impact of dose metameter misspecification on test efficiency.

Main Methods:

Related Experiment Videos

  • Comparative analysis of Jonckheere-Terpstra and Poisson tests (robust, conditional).
  • Evaluation of small and large sample performance.
  • Simulations under conditions of no trend, dose-related trend, Poisson, and overdispersed Poisson data.
  • Assessment of dose metameter misspecification effects.

    • Main Results:

    • Poisson test is suitable for data with minimal overdispersion.
    • For highly overdispersed data (response rate < 2-3), the robust Poisson test is recommended.
    • For moderately dispersed or continuous data (average responses > 2-3), the robust Poisson or Jonckheere-Terpstra test is advised.
    • Dose metameter misspecification significantly impacts test efficiency.

    Conclusions:

    • Test selection for dose-related trend detection in toxicology depends on data overdispersion and discreteness.
    • Robust Poisson and Jonckheere-Terpstra tests offer alternatives for overdispersed data.
    • Using equally spaced dose levels is generally recommended for Poisson and robust Poisson trend tests unless specific reasons dictate otherwise.