Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

On tests against one-sided hypotheses in some generalized linear models

M J Silvapulle1

  • 1School of Agriculture, La Trobe University, Bundoora, Australia.

Biometrics
|September 1, 1994
PubMed
Summary

One-sided hypothesis testing offers increased statistical power by utilizing directional information. This study demonstrates the asymptotic equivalence of various one-sided tests in generalized linear and Cox regression models.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Tests against qualitative interaction: exact critical values and robust tests.

Biometrics·2002
Same author

Ladders: accidents waiting to happen.

The Medical journal of Australia·2001
Same author

Epileptology of the first-seizure presentation: a clinical, electroencephalographic, and magnetic resonance imaging study of 300 consecutive patients.

Lancet (London, England)·1998
Same author

Epidermal growth factor alters the electrolyte profile of lactating ewes (Ovis aries).

Comparative biochemistry and physiology. Comparative physiology·1992
Same author

Fluid balance, electrolyte profiles and plasma parathyroid hormone concentrations in ewes treated with epidermal growth factor.

The Journal of endocrinology·1992
Same author

On testing for threshold values.

Biometrics·1991

Area of Science:

  • Biostatistics
  • Statistical Modeling
  • Regression Analysis

Background:

  • One-sided hypotheses are common in scientific research, necessitating specialized testing.
  • Standard two-sided tests may not fully leverage available directional information.
  • Increasing statistical power is a key objective in hypothesis testing.

Purpose of the Study:

  • To evaluate the performance of various one-sided hypothesis tests.
  • To demonstrate the asymptotic equivalence of these tests in terms of local power.
  • To extend known results for two-sided alternatives to one-sided scenarios.

Main Methods:

  • Consideration of likelihood ratio, Wald, score, generalized distance, and Pearson chi-square test statistics.
  • Analysis within a class of models including generalized linear and Cox regression.

Related Experiment Videos

  • Asymptotic analysis of local power for different test statistics.

    • Main Results:

    • The analyzed one-sided test statistics demonstrate asymptotic equivalence in local power.
    • This equivalence generalizes findings previously established for two-sided hypothesis testing.
    • The study provides a theoretical foundation for choosing among these tests.

    Conclusions:

    • One-sided tests effectively utilize directional information, enhancing statistical power.
    • The asymptotic equivalence simplifies test selection in generalized linear and Cox models.
    • Applications include testing interactions in binomial models and comparing ordinal responses.