Evidence map›Paper›PMID 30950737›Full record

ArticleJournal of speech, language, and hearing research : JSLHR2019

How Mixed-Effects Modeling Can Advance Our Understanding of Learning and Memory and Improve Clinical and Educational Practice.

Katherine R Gordon

Abstract read
In one paragraph

Article in Journal of speech, language, and hearing research : JSLHR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Capturing the Heterogeneity of Word Learners by Analyzing Persons.Behavioral sciences (Basel, Switzerland) · 2024
    Article
  3. Article
  4. Auditory, Lexical, and Multitasking Demands Interactively Impact Listening Effort.Journal of speech, language, and hearing research : JSLHR · 2023
    Article
  5. Reproducibility in Small-Journal of speech, language, and hearing research : JSLHR · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Effects of Gap Position on Perceptual Gap Detection Across Late Childhood and Adolescence.Journal of the Association for Research in Otolaryngology : JARO · 2020
    Article
  13. Article
  14. Article
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

1 author.

Katherine R GordonCenter for Childhood Deafness, Language, and Learning Research, Boys Town National Research Hospital, Omaha, NE.

Funding

The Impact of Mild Hearing Loss on Auditory Perception in Complex EnvironmentsP20GM109023 · NIGMS · FATHER FLANAGAN'S BOYS' HOME · PI CHATTERJEE, MONITA · 2014 to 2023
$23.4M
Long-Term Retention of Words by Children with Language ImpairmentR21DC016130 · NIDCD · FATHER FLANAGAN'S BOYS' HOME · PI GORDON, KATHERINE RUTH · 2017 to 2019
$452k
Context Effects on Word Learning and GeneralizationF32DC013704 · NIDCD · UNIVERSITY OF IOWA · PI GORDON, KATHERINE RUTH · 2014 to 2016
$167k
NIDCD NIH HHS F32 DC013704NIDCD NIH HHS R21 DC016130NIGMS NIH HHS P20 GM109023
6 · The paper itself

Abstract

Purpose A key goal of researchers, clinicians, and educators within the fields of speech, language, and hearing sciences is to support the learning and memory of others. To do so, they consider factors relevant to the individual, the material to be learned, and the training strategy that can maximize learning and retention. Statistical methods typically used within these fields are inadequate for identifying the complex relationships between these factors and are ill equipped to account for variability across individuals when identifying these relationships. Specifically, traditional statistical methods are often inadequate for answering questions about special populations because samples drawn from these populations are usually small, highly variable, and skewed in distribution. Mixed-effects modeling provides advantages over traditional statistical techniques to answer complex questions while taking into account these common characteristics of special populations. Method and Results Through 2 examples, I illustrate advantages of mixed-effects modeling in answering questions about learning and memory and in supporting better translation of research to practice. I also demonstrate key similarities and differences between analysis of variance, regression analyses, and mixed-effects modeling. Finally, I explain 3 additional advantages of using mixed-effects modeling to understand the processes of learning and memory: the means to account for missing data, assess the contribution of variations in delay intervals, and model nonlinear relationships between factors. Conclusions Through mixed-effects modeling, researchers can disseminate accurate information about learning and memory to clinicians and educators. In turn, through enhanced statistical literacy, clinicians and educators can apply research findings to practice with confidence. Overall, mixed-effects modeling is a powerful tool to improve the outcomes of the individuals that researchers and practitioners serve within the fields of speech, language, and hearing sciences.

Indexed as

LearningMemoryModels, StatisticalBehavioral ResearchEducation, SpecialHearing DisordersHumansLanguage DisordersSpeech DisordersStatistics as Topic

Identifiers

PMID30950737
PMCPMC6802904

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.