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

A mixed-effects model for categorical data.

P J Beitler, J R Landis

    Biometrics
    |December 1, 1985
    PubMed
    Summary
    This summary is machine-generated.

    A new mixed model for categorical data handles unbalanced study designs, similar to ANOVA for quantitative data. This method accurately estimates variance components and tests treatment effects in complex clinical trials.

    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

    Correlates of 1-Year Change in Quality of Life in Patients with Urologic Chronic Pelvic Pain Syndrome: Findings from the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network.

    The Journal of urology·2020
    Same author

    Urinalysis in patients with neuromyelitis optica spectrum disorder.

    European journal of neurology·2019
    Same author

    Randomized multicenter clinical trial of myofascial physical therapy in women with interstitial cystitis/painful bladder syndrome and pelvic floor tenderness.

    The Journal of urology·2012
    Same author

    Variability of creatinine measurements in clinical laboratories: results from the CRIC study.

    American journal of nephrology·2010
    Same author

    Rescoring the NIH chronic prostatitis symptom index: nothing new.

    Prostate cancer and prostatic diseases·2009
    Same author

    A pilot clinical trial of oral pentosan polysulfate and oral hydroxyzine in patients with interstitial cystitis.

    The Journal of urology·2003
    Same journal

    Fast penalized generalized estimating equations for large longitudinal functional datasets.

    Biometrics·2026
    Same journal

    Causally-interpretable random-effects meta-analysis.

    Biometrics·2026
    Same journal

    Statistical inference for mean function of partially observed functional time series.

    Biometrics·2026
    Same journal

    Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

    Biometrics·2026
    Same journal

    Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

    Biometrics·2026
    Same journal

    Discussion on "INTACT: a method for integration of longitudinal physical activity data from multiple sources" by Jingru Zhang, Erjia Cui, Hongzhe Li, and Haochang Shou.

    Biometrics·2026
    See all related articles

    Area of Science:

    • Statistics
    • Biostatistics
    • Clinical Trials

    Background:

    • Analyzing categorical data in unbalanced study designs presents statistical challenges.
    • Existing methods may not adequately handle complex structures like those in multicenter trials.

    Purpose of the Study:

    • To propose a novel mixed model for categorical data analogous to two-way ANOVA for quantitative data.
    • To develop a method for estimating variance components and testing treatment differences in unbalanced designs.

    Main Methods:

    • An extension of the fitting constants method was used to estimate variance components.
    • Reductions in sums of squares were employed for variance component estimation.
    • A Wald statistic within a general linear model framework was utilized for hypothesis testing.

    Related Experiment Videos

    Main Results:

    • The proposed mixed model effectively handles categorical data from unbalanced designs.
    • Variance component estimators were successfully derived using the fitting constants method.
    • The methodology was illustrated using data from a multicenter clinical trial.

    Conclusions:

    • The developed mixed model provides a robust approach for analyzing categorical outcomes in unbalanced experimental settings.
    • This method is particularly applicable to complex clinical trial data with fixed and random effects.