Jove
Visualize
Contact Us

Related Experiment Videos

Worm plot: a simple diagnostic device for modelling growth reference curves.

S van Buuren1, M Fredriks

  • 1Department of Statistics, TNO Prevention and Health, Leiden, P.O. Box 2215, 2301 CE Leiden, The Netherlands. S.vanBuuren@pg.tno.nl

Statistics in Medicine
|April 17, 2001
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

Multiple imputation in data that grow over time: a comparison of three strategies.

Multivariate behavioral research·2021
Same author

Equality Constraints in Multiple Correspondence Analysis.

Multivariate behavioral research·2016
Same author

Adolescent growth: genes, hormones and the peer group. Proceedings of the 20th Aschauer Soiree, held at Glücksburg castle, Germany, 15th to 17th November 2013.

Pediatric endocrinology reviews : PER·2014
Same author

Estimation of caries experience by multiple imputation and direct standardization.

Caries research·2013
Same author

Reference chart of inspiratory muscle strength: a new tool to monitor the effect of pre-operative training.

Physiotherapy·2013
Same author

Personalized approach to growth hormone treatment: clinical use of growth prediction models.

Hormone research in paediatrics·2013
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
Same journal

Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.

Statistics in medicine·2026
See all related articles
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

The worm plot is a diagnostic tool that helps create accurate growth reference curves by assessing data normality. It aids in refining the LMS model for better age-conditional mean and skewness modeling in anthropometric studies.

Area of Science:

  • Statistics
  • Biostatistics
  • Growth Monitoring

Background:

  • Growth reference curves are essential for monitoring child development.
  • The LMS model provides a flexible framework for constructing these curves.
  • Assessing the fit of the LMS model, particularly age-conditional normality, is crucial for accurate curve generation.

Purpose of the Study:

  • To introduce and evaluate the worm plot as a diagnostic tool for assessing age-conditional normality in the context of growth reference curve construction.
  • To demonstrate the application of the worm plot in refining the LMS model parameters for the Fourth Dutch Growth Study.
  • To compare the performance of the LMS model in capturing different aspects of data distribution (mean, skewness, variation, kurtosis).

Main Methods:

Related Experiment Videos

  • Utilized the worm plot to visualize differences between observed and expected distributions of transformed anthropometric data.
  • Applied the LMS (Lambda, Mu, Sigma) model, with age-dependent smooth parameter curves for median, variation, and skewness.
  • Assessed the fit of various LMS models by examining features of the worm plot, such as offset, slope, and curvature.

    • Main Results:

    • The worm plot effectively assessed age-conditional normality of transformed data under different LMS models.
    • Application to the Dutch Growth Study data yielded satisfactory anthropometric reference curves.
    • The LMS method demonstrated superior performance in modeling age-conditional mean and skewness compared to variation and kurtosis.

    Conclusions:

    • The worm plot is a valuable tool for diagnostic checks in growth curve modeling.
    • The LMS model, when refined using worm plot diagnostics, provides reliable growth reference curves.
    • The study highlights the importance of assessing age-conditional normality for accurate anthropometric data analysis.