scholarly journals The Structure of Developmental Variation in Early Childhood

2021 ◽  
Author(s):  
Ben Stenhaug ◽  
Nilam Ram ◽  
Michael C. Frank
Keyword(s):  
Early Childhood ◽  
Item Response ◽  
Empirical Work ◽  
Developmental Changes ◽  
Older Children ◽  
Developmental Variation ◽  
Higher Dimensional ◽  
Infancy And Early Childhood ◽  
Developmental Differentiation ◽  
Item Response Theory Models

Do children’s abilities develop in tandem or on their own separate timetables? Piaget proposed that development proceeded globally through stages; more recent theories view development as more modular with different abilities developing independently and on different time-scales. The developmental differentiation hypothesis suggests that the structure of a child’s development is unitary early in infancy but becomes more complex with age. Despite an abundance of theoretical interest in this question, there is little empirical work on the macrostructure of developmental changes in early childhood. We investigate this structure using two large datasets of parent-reported developmental milestones. Applying item response theory models, we find that variation in development across infancy and early childhood is multidimensional. Consistent with the differentiation hypothesis, differences among older children are better described by higher-dimensional models. In addition, in longitudinal data, we find that, within-person changes in underlying abilities are highly coupled early in life but their coupling decreases by age 12 months. Our work provides a model-based method for linking holistic descriptions of early development to basic theoretical questions about the nature of change in childhood.

scholarly journals Toward a “Standard Model” of Early Language Learning

2021 ◽  
Author(s):  
George Kachergis ◽  
Virginia A. Marchman ◽  
Michael C. Frank
Keyword(s):  
Standard Model ◽  
Language Learning ◽  
Learning Outcomes ◽  
Item Response ◽  
Computational Models ◽  
Empirical Work ◽  
Individual Variability ◽  
Early Language ◽  
Accumulator Models ◽  
Item Response Theory Models

A "standard model" is a theoretical framework that synthesizes observables into a quantitative consensus. Have we made progress towards this kind of synthesis for children’s early language learning? Many computational models of early vocabulary learning assume that individual words are learned through an accumulation of environmental input. This assumption is also implicit in empirical work that emphasizes links between language input and learning outcomes. However, models have typically focused on average performance, while empirical work has focused on variability. To model individual variability, we relate the tradition of research on accumulator models to Item-Response Theory models from psychometrics. This formal connection reveals that currently available datasets cannot allow us to fully test these models, illustrating a critical need for theory in shaping new data collection and in creating and testing an eventual "standard model."

scholarly journals Long term alterations of growth after antenatal steroids in preterm twin pregnancies

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Thorsten Braun ◽  
Vivien Filleböck ◽  
Boris Metze ◽  
Christoph Bührer ◽  
Andreas Plagemann ◽  
...  
Keyword(s):  
Early Childhood ◽  
Disease Risk ◽  
Later Life ◽  
Ponderal Index ◽  
Childhood Growth ◽  
Antenatal Steroids ◽  
Increased Risk ◽  
Infancy And Early Childhood ◽  
Twin Pregnancies

AbstractObjectivesTo compare the long-term effects of antenatal betamethasone (ANS, ≤16 mg, =24 mg and >24 mg) in twins on infant and childhood growth.MethodsA retrospective cohort follow up study among 198 twins after ANS including three time points: U1 first neonatal examination after birth and in the neonatal period; U7 examination from the 21st to the 24th month of life and U9 examination from the 60th to the 64th month of life using data from copies of the children’s examination booklets. Inclusion criteria are twin pregnancies with preterm labor, cervical shortening, preterm premature rupture of membranes, or vaginal bleeding, and exposure to ANS between 23+5 and 33+6 weeks. Outcome measures are dosage-dependent and sex-specific effects of ANS on growth (body weight, body length, head circumference, body mass index and ponderal index) up to 5.3 years.ResultsOverall, 99 live-born twin pairs were included. Negative effects of ANS on fetal growth persisted beyond birth, altered infant and childhood growth, independent of possible confounding factors. Overall weight percentile significantly decreased between infancy and early childhood by 18.8%. Birth weight percentiles significantly changed in a dose dependent and sex specific manner, most obviously in female-female and mixed pairs. The ponderal index significantly decreased up to 42.9%, BMI index increased by up to 33.8%.ConclusionsANS results in long-term alterations in infant and childhood growth. Changes between infancy and early childhood in ponderal mass index and BMI, independent of dose or twin pair structure, might indicate an ANS associated increased risk for later life disease.SynopsisFirst-time report on long-term ANS administration growth effects in twin pregnancies, showing persisting alterations beyond birth in infant and childhood growth up to 5.3 years as potential indicator of later life disease risk.

scholarly journals HGG-34. DETECTION OF ONCOGENIC FUSION EVENTS IN SUPRATENTORIAL GLIOBLASTOMAS OF YOUNG CHILDREN

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii349-iii350
Author(s):  
Torsten Pietsch ◽  
Christian Vokuhl ◽  
Gerrit H Gielen ◽  
Andre O von Bueren ◽  
Everlyn Dörner ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Rna Sequencing ◽  
First Year ◽  
Gene Fusions ◽  
Older Children ◽  
Kinase Gene ◽  
Dna And Rna ◽  
Infancy And Early Childhood ◽  
Stable Genome ◽  
First Year Of Life

Abstract INTRODUCTION Glioblastoma in infancy and early childhood is characterized by a more favorable outcome compared to older children, a stable genome, and the occurrence of tyrosine kinase gene fusions that may represent therapeutic targets. METHODS 50 glioblastomas (GBM) with supratentorial location occurring in children younger than four years were retrieved from the archives of the Brain Tumor Reference Center, Institute of Neuropathology, University of Bonn. DNA and RNA were extracted from FFPE tumor samples. Gene fusions were identified by FISH using break-apart probes for ALK, NTRK1, -2, -3, ROS1 and MET, Molecular Inversion Probe (MIP) methodology, and targeted RNA sequencing. RESULTS 37 supratentorial GBM occurred in the first year of life, 13 GBM between one and four years. 18 cases showed fusions of ALK to different fusion partners; all occurred in the first year of life (18/37 cases, 48.6%). Fusions of ROS1 were found in 5, MET in 3, NTRK1, -2, -3 in 10 cases. 12 cases showed no and two novel fusions. The different methods led to comparable results; targeted RNA sequencing was not successful in a fraction of cases. Break-apart FISH led to reliable results on the next day, MIP technology represented the most sensitive method for analysis of FFPE samples. CONCLUSIONS Gene fusions involving the tyrosine kinase genes ALK, MET, ROS1 and NTRK1, -2, -3 occurred in 72% of glioblastomas of children younger than four years; the most frequent were ALK fusions occurring in infant GBM. DNA based MIP technology represented the most robust and sensitive assay.

scholarly journals Introducing the StataStan Interface for Fast, Complex Bayesian Modeling Using Stan

2017 ◽  
Vol 17 (2) ◽  
pp. 330-342 ◽  
Author(s):  
Robert L. Grant ◽  
Bob Carpenter ◽  
Daniel C. Furr ◽  
Andrew Gelman
Keyword(s):  
Bayesian Inference ◽  
Item Response Theory ◽  
Open Source ◽  
Item Response ◽  
Bayesian Modeling ◽  
Inference Engine ◽  
Software Components ◽  
Statistical Software ◽  
Simulation Based ◽  
Item Response Theory Models

In this article, we present StataStan, an interface that allows simulation-based Bayesian inference in Stata via calls to Stan, the flexible, open-source Bayesian inference engine. Stan is written in C++, and Stata users can use the commands stan and windowsmonitor to run Stan programs from within Stata. We provide a brief overview of Bayesian algorithms, details of the commands available from Statistical Software Components, considerations for users who are new to Stan, and a simple example. Stan uses a different algorithm than bayesmh, BUGS, JAGS, SAS, and MLwiN. This algorithm provides considerable improvements in efficiency and speed. In a companion article, we give an extended comparison of StataStan and bayesmh in the context of item response theory models.

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