Literature DB >> 30950745

Essential Statistical Concepts for Research in Speech, Language, and Hearing Sciences.

Jacob J Oleson1, Grant D Brown1, Ryan McCreery2.   

Abstract

Purpose Clinicians depend on the accuracy of research in the speech, language, and hearing sciences to improve assessment and treatment of patients with communication disorders. Although this work has contributed to great advances in clinical care, common statistical misconceptions remain, which deserve closer inspection in the field. Challenges in applying and interpreting traditional statistical methods with behavioral data from humans have led to difficulties with replication and reproducibility in other allied scientific fields, including psychology and medicine. The importance of research in our fields of study for advancing science and clinical care for our patients means that the choices of statistical methods can have far-reaching, real-world implications. Method The goal of this article is to provide an overview of fundamental statistical concepts and methods that are used in the speech, language, and hearing sciences. Results We reintroduce basic statistical terms such as the p value and effect size, as well as recommended procedures for model selection and multiple comparisons. Conclusions Research in the speech, language, and hearing sciences can have a profound positive impact on the lives of individuals with communication disorders, but the validity of scientific findings in our fields is enhanced when data are analyzed using sound statistical methods. Misunderstanding or misinterpretation of basic statistical principles may erode public trust in research findings. Recommendations for practices that can help minimize the likelihood of errors in statistical inference are provided. Supplemental Material https://doi.org/10.23641/asha.7849223.

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Year:  2019        PMID: 30950745      PMCID: PMC6802903          DOI: 10.1044/2018_JSLHR-S-ASTM-18-0239

Source DB:  PubMed          Journal:  J Speech Lang Hear Res        ISSN: 1092-4388            Impact factor:   2.297


  13 in total

1.  Contradicted and initially stronger effects in highly cited clinical research.

Authors:  John P A Ioannidis
Journal:  JAMA       Date:  2005-07-13       Impact factor: 56.272

2.  Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods.

Authors:  M Aickin; H Gensler
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Authors:  Harold Pashler; Eric-Jan Wagenmakers
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4.  Bayesian Applications in Auditory Research.

Authors:  Garnett P McMillan; John B Cannon
Journal:  J Speech Lang Hear Res       Date:  2019-03-25       Impact factor: 2.297

5.  Timeliness of service delivery for children with later-identified mild-to-severe hearing loss.

Authors:  Elizabeth A Walker; Lenore Holte; Meredith Spratford; Jacob Oleson; Anne Welhaven; Melody Harrison
Journal:  Am J Audiol       Date:  2014-03       Impact factor: 1.493

6.  Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli.

Authors:  Jacob Westfall; David A Kenny; Charles M Judd
Journal:  J Exp Psychol Gen       Date:  2014-08-11

7.  Multiple comparison procedures.

Authors:  Jing Cao; Song Zhang
Journal:  JAMA       Date:  2014-08-06       Impact factor: 56.272

8.  The Proposal to Lower P Value Thresholds to .005.

Authors:  John P A Ioannidis
Journal:  JAMA       Date:  2018-04-10       Impact factor: 56.272

9.  A Practical Guide to Calculating Cohen's f(2), a Measure of Local Effect Size, from PROC MIXED.

Authors:  Arielle S Selya; Jennifer S Rose; Lisa C Dierker; Donald Hedeker; Robin J Mermelstein
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10.  The prevalence of statistical reporting errors in psychology (1985-2013).

Authors:  Michèle B Nuijten; Chris H J Hartgerink; Marcel A L M van Assen; Sacha Epskamp; Jelte M Wicherts
Journal:  Behav Res Methods       Date:  2016-12
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  7 in total

Review 1.  The Evolution of Statistical Methods in Speech, Language, and Hearing Sciences.

Authors:  Jacob J Oleson; Grant D Brown; Ryan McCreery
Journal:  J Speech Lang Hear Res       Date:  2019-03-25       Impact factor: 2.297

Review 2.  Statistical Considerations for Analyzing Ecological Momentary Assessment Data.

Authors:  Jacob J Oleson; Michelle A Jones; Erik J Jorgensen; Yu-Hsiang Wu
Journal:  J Speech Lang Hear Res       Date:  2021-12-15       Impact factor: 2.674

3.  Assessing Language in Unstructured Conversation in People With Aphasia: Methods, Psychometric Integrity, Normative Data, and Comparison to a Structured Narrative Task.

Authors:  Marion C Leaman; Lisa A Edmonds
Journal:  J Speech Lang Hear Res       Date:  2021-10-07       Impact factor: 2.674

4.  Effect of level on spectral-ripple detection threshold for listeners with normal hearing and hearing loss.

Authors:  Erik J Jorgensen; Ryan W McCreery; Benjamin J Kirby; Marc Brennan
Journal:  J Acoust Soc Am       Date:  2020-08       Impact factor: 1.840

5.  Comparisons of the Sensitivity and Reliability of Multiple Measures of Listening Effort.

Authors:  Nicholas P Giuliani; Carolyn J Brown; Yu-Hsiang Wu
Journal:  Ear Hear       Date:  2021 Mar/Apr       Impact factor: 3.562

6.  Comparison of In-Situ and Retrospective Self-Reports on Assessing Hearing Aid Outcomes.

Authors:  Yu-Hsiang Wu; Elizabeth Stangl; Octav Chipara; Anna Gudjonsdottir; Jacob Oleson; Ruth Bentler
Journal:  J Am Acad Audiol       Date:  2020-12-15       Impact factor: 1.245

7.  Passive case detection for canine visceral leishmaniasis control in urban Brazil: Determinants of population uptake.

Authors:  João Gabriel G Luz; Amanda G de Carvalho; João Victor L Dias; Luis Claudio L Marciano; Sake J de Vlas; Cor Jesus F Fontes; Luc E Coffeng
Journal:  PLoS Negl Trop Dis       Date:  2021-10-08
  7 in total

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