Figure 2 from Estimating Growth in Height from Limited Longitudinal Growth Data Using Full-Curves Training Dataset: A Comparison of Two Procedures of Curve Optimization—Functional Principal Component Analysis and SITAR | Semantic Scholar (2024)

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This paper proposes a computationally effective estimator of large functional and longitudinal data within the framework of FLMM, in which all the parameters can be automatically estimated and proves that the mean function estimation and individual trajectory prediction reach the minimax lower bounds of all nonparametric estimations.

Average ages at TO and PHV were similar with SITAR and FPCA, and ages at PHV were most strongly correlated with SA at ~14 years, and mean ages at PHV showed a north-south gradient among European samples, and were later compared to Japanese samples.

Relationships between physical similarity of parents and the descriptors of the growth curves of their offspring were found, however, parental similarity in various features affected the growth of their children differently.

Regular monitoring of growth seems important to detect players at higher risk for being disrupted by growth-related injuries and to calculate overall and specific injury burden in circa- and post-PHV elite academy soccer players.

This study compared the results of ameta-analysis of intersex differences in radioulnar contrasts between published mean values of dermatoglyphic ridge counts on the fingers of the hand (calculated from the higher RC of each finger) with intersex Differences obtained from radioular contrasts already calculated at the individual level.

This erratum has corrected three mistakes in the original manuscript in the direct calculation of peak height velocity and age at take-off and has implemented the solutions in a STATA program which directly calculates the estimates, standard errors and confidence intervals for age, height and velocity at peak height Velocity.

The model is used to fit weight data for 602 infants, measured from 0 to 2 years as part of the Childhood Asthma Prevention Study (CAPS) trial, and to determine the effect of breastfeeding on infant weight.

A new family of mathematical functions to fit longitudinal growth data is described, containing only five parameters to describe growth in stature from age two to maturity.

The method of Dynamic Phenotypes may be helpful for investigation of the brain's function ontogeny in relation to neural and humoral regulatory mechanisms of body mass growth during childhood and transition into puberty.

A new approach to modelling the individual human linear growth curve from birth to maturity is presented in detail, which provides an improved instrument for detecting and understanding growth failure and sheds light on some central facets of human growth.

Although the cross-validation meets statistical standards for acceptance, caution is warranted with regard to implementation and it is recommended that maturity offset be considered as a categorical rather than a continuous assessment.

The combination of PCA and the Maximum Likelihood Principle provides a new, powerful and automatic tool for growth modelling that includes estimates of future growth, adult stature and developmental tempo.

The sex-specific regression equations developed using anthropometric measures to predict somatic maturity provided good fits in external samples and provide an alternative to commonly used models.

The mixed effects models perform well in estimating timing and intensity in individuals across several puberty markers, and age at peak velocity correlates highly across markers, but peak velocity less so.

Care is warranted in utilizing maturity offset per se and predicted age at PHV based on maturity offset as an indicator of maturity timing in female gymnasts and perhaps other short females.

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