Evidence map›Paper›PMID 34266565›Full record

ReviewAdvances in child development and behavior2021

Building theories of consistency and variability in children's language development: A large-scale data approach.

Angeline Sin Mei Tsui, Virginia A Marchman, Michael C Frank

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Advances in child development and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Angeline Sin Mei TsuiDepartment of Psychology, Stanford University, Stanford, CA, United States. Electronic address: angelinetsui@gmail.com.
Virginia A MarchmanDepartment of Psychology, Stanford University, Stanford, CA, United States.
Michael C FrankDepartment of Psychology, Stanford University, Stanford, CA, United States.

Funding

Predicting language processing efficiency in preterm children: Social-environmental and neuro-biological factorsR01HD069150 · NICHD · STANFORD UNIVERSITY · PI FELDMAN, HEIDI M. · 2011 to 2024
$5.8M
Early language processing skill and school-relevant outcomes in emerging bilingual studentsR01HD092343 · NICHD · STANFORD UNIVERSITY · PI FERNALD, ANNE · 2017 to 2021
$2.7M
NICHD NIH HHS R01 HD069150NICHD NIH HHS R01 HD092343
6 · The paper itself

Abstract

Young children typically begin learning words during their first 2 years of life. On the other hand, they also vary substantially in their language learning. Similarities and differences in language learning call for a quantitative theory that can predict and explain which aspects of early language are consistent and which are variable. However, current developmental research practices limit our ability to build such quantitative theories because of small sample sizes and challenges related to reproducibility and replicability. In this chapter, we suggest that three approaches-meta-analysis, multi-site collaborations, and secondary data aggregation-can together address some of the limitations of current research in the developmental area. We review the strengths and limitations of each approach and end by discussing the potential impacts of combining these three approaches.

Indexed as

LanguageLearningChildChild, PreschoolHumansLanguage DevelopmentReproducibility of ResultsLarge-scale datasetsMeta-analysisMultisite studiesReplicationTheory-building

Identifiers

PMID34266565
PMCPMC8905594

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.