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

Recommendations for appropriate statistical practice in toxicologic experiments.

K E Muller, C N Barton, V A Benignus

    Neurotoxicology
    |January 1, 1984
    PubMed
    Summary
    This summary is machine-generated.

    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

    Prevalence of disorders in preweaned dairy calves from 731 dairies in Germany: A cross-sectional study.

    Journal of dairy science·2021
    Same author

    Factors associated with calf mortality and poor growth of dairy heifer calves in northeast Germany.

    Preventive veterinary medicine·2020
    Same author

    Elevated markers of gut leakage and inflammasome activation in COVID-19 patients with cardiac involvement.

    Journal of internal medicine·2020
    Same author

    Distinct and early increase in circulating MMP-9 in COVID-19 patients with respiratory failure.

    The Journal of infection·2020
    Same author

    Calculating Power for the General Linear Multivariate Model With One or More Gaussian Covariates.

    Communications in statistics: theory and methods·2019
    Same author

    On the Distribution of Summary Statistics for Missing Data.

    Communications in statistics: theory and methods·2019
    Same journal

    Urinary Volatile Organic Compound Metabolites and Depressive Symptoms Among U.S. Adults With Cardiovascular-Kidney-Metabolic Syndrome Stages 0-3: NHANES-Based Associations and In Silico Multi-Omics Insights.

    Neurotoxicology·2026
    Same journal

    PM<sub>2.5</sub>-bound organophosphate esters and childhood attention-deficit hyperactivity disorder symptoms: A population-based study from China.

    Neurotoxicology·2026
    Same journal

    Paternal Exposure to Chlorpyrifos Disrupts Protein Regulation and Abolishes PKCβ Signaling in Learning‑Related Neural Circuits.

    Neurotoxicology·2026
    Same journal

    Zebrafish Behavioral Assessment as a First-Tier Whole-Organism NAM for Developmental Neurotoxicity: A Multi-Laboratory Evaluation.

    Neurotoxicology·2026
    Same journal

    Adolescent prefrontal and amygdala molecular signatures of perinatal morphine versus buprenorphine exposure in mice.

    Neurotoxicology·2026
    Same journal

    A multiparametric 3D cortical neurosphere NAM for developmental neurotoxicity: Chlorpyrifos and a biomonitoring-anchored PFAS mixture.

    Neurotoxicology·2026
    See all related articles

    This review highlights statistical challenges in toxicology, emphasizing the need for robust methods to accurately identify toxic effects while minimizing false accusations against safe compounds. Strategies like top-down planning and efficient experimental design are crucial for reliable toxicologic research.

    Area of Science:

    • Toxicologic research
    • Statistical methodology

    Background:

    • Balancing the detection of toxic effects with the accurate assessment of harmless compounds is a key challenge in toxicologic research.
    • Distortion of error rates can arise from multiple dependent variables, excessive testing, data snooping, low statistical power, and violated statistical assumptions.

    Purpose of the Study:

    • To review appropriate statistical practices in toxicologic research.
    • To identify common problems that distort error rates in toxicologic studies.
    • To propose solution strategies for improving statistical rigor.

    Main Methods:

    • Review of statistical practices in toxicologic research.
    • Identification of factors affecting error rates.
    • Discussion of strategies for appropriate statistical analysis.

    Related Experiment Videos

    Main Results:

    • Multiple factors, including numerous variables, extensive testing, data snooping, insufficient statistical power, and assumption violations, can distort error rates.
    • Effective strategies involve comprehensive planning, efficient experimental design, balancing Type I and Type II errors, hypothesis selection, and appropriate statistical analyses.

    Conclusions:

    • Top-down planning and the "leapfrog" design strategy are particularly emphasized as effective approaches.
    • Adoption of these statistical practices is essential for the integrity of toxicologic research and the reliable identification of toxic substances.