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

Some nonparametric statistical tests for quick evaluation of clinical data.

E M Gindler

    Clinical Chemistry
    |March 1, 1975
    PubMed
    Summary

    Rapid statistical tests quickly assess method agreement and data distribution. Unusual patient test value distributions may signal laboratory errors or specimen issues.

    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

    Least-squares evaluation of linearity.

    Clinical chemistry·1979
    Same author

    A new noncorrosive dye reagent for automatic sugar chromatography.

    Analytical biochemistry·1973
    Same author

    Rapid colorimetric determination of calcium in biologic fluids with methylthymol blue.

    American journal of clinical pathology·1972
    Same author

    Nomogram for calculation of creatinine clearance.

    Clinical chemistry·1970
    Same author

    Nomograms for calculation of urea clearance.

    Clinical chemistry·1970
    Same author

    Nomogram for calculation of concentration for colorimetric systems in which absorbance decreases linearly as concentration increases.

    Clinical chemistry·1970

    Area of Science:

    • Clinical Chemistry
    • Biostatistics
    • Laboratory Medicine

    Background:

    • Statistical methods are crucial for evaluating laboratory test performance and data integrity.
    • Identifying deviations from expected data distributions can indicate critical issues in laboratory processes.

    Purpose of the Study:

    • To introduce rapid statistical tests for evaluating laboratory method agreement and data distribution.
    • To highlight the utility of these tests in detecting potential laboratory errors or sample quality problems.

    Main Methods:

    • Utilizes rapid statistical tests such as sign tests, run tests, and Tukey's quick test.
    • These methods primarily involve data counting and the application of nomograms for analysis.

    Main Results:

    • These tests provide quick assessments of how well different laboratory methods agree.
    • They also facilitate the evaluation of the distribution of test results, aiding in anomaly detection.

    Conclusions:

    • Rapid statistical tests offer efficient tools for routine laboratory quality control.
    • Anomalous distributions in patient test values warrant investigation for potential errors or unique patient factors.

    Related Experiment Videos