Evidence map›Paper›PMID 39153045›Full record

ArticleDysphagia2025

Effects of Statistical Practices for Longitudinal Group Comparison of the Penetration-Aspiration Scale on Power and Effect Size Estimation: A Monte Carlo Simulation Study.

James C Borders, Alessandro A Grande, Carly E A Barbon, Katherine A Hutcheson, Michelle S Troche

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In one paragraph

Article in Dysphagia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Observational
  3. Review
  4. 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

5 authors.

James C BordersLaboratory for the Study of Upper Airway Dysfunction, Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, NY, USA. jcb2271@tc.columbia.edu.ORCID 0000-0002-0291-4266
Alessandro A GrandeDepartment of Statistics, Columbia University, New York, NY, USA.
Carly E A BarbonDepartment of Head and Neck Surgery, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Katherine A HutchesonDepartment of Head and Neck Surgery, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Michelle S TrocheLaboratory for the Study of Upper Airway Dysfunction, Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, NY, USA.

Funding

Council of Academic Programs in Communication Sciences and Disorders Council of Academic Programs in Communication Sciences and Disorders
6 · The paper itself

Abstract

Multiple bolus trials are administered during clinical and research swallowing assessments to comprehensively capture an individual's swallowing function. Despite valuable information obtained from these boluses, it remains common practice to use a single bolus (e.g., the worst score) to describe the degree of dysfunction. Researchers also often collapse continuous or ordinal swallowing measures into categories, potentially exacerbating information loss. These practices may adversely affect statistical power to detect and estimate smaller, yet potentially meaningful, treatment effects. This study sought to examine the impact of aggregating and categorizing penetration-aspiration scale (PAS) scores on statistical power and effect size estimates. We used a Monte Carlo approach to simulate three hypothetical within-subject treatment studies in Parkinson's disease and head and neck cancer across a range of data characteristics (e.g., sample size, number of bolus trials, variability). Different statistical models (aggregated or multilevel) as well as various PAS reduction approaches (i.e., types of categorizations) were performed to examine their impact on power and the accuracy of effect size estimates. Across all scenarios, multilevel models demonstrated higher statistical power to detect group-level longitudinal change and more accurate estimates compared to aggregated (worst score) models. Categorizing PAS scores also reduced power and biased effect size estimates compared to an ordinal approach, though this depended on the type of categorization and baseline PAS distribution. Multilevel models should be considered as a more robust approach for the statistical analysis of multiple boluses administered in standardized swallowing protocols due to its high sensitivity and accuracy to compare group-level changes in swallowing function. Importantly, this finding appears to be consistent across patient populations with distinct pathophysiology (i.e., PD and HNC) and patterns of airway invasion. The decision to categorize a continuous or ordinal outcome should be grounded in the clinical or research question with recognition that scale reduction may negatively affect the quality of statistical inferences in certain scenarios.

Indexed as

DeglutitionDeglutition DisordersRespiratory AspirationHead and Neck NeoplasmsHumansLongitudinal StudiesModels, StatisticalMonte Carlo MethodParkinson DiseaseSeverity of Illness IndexDeglutition disordersDysphagiaMeta-scienceMultilevel modelsStatistics

Identifiers

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Registered trials

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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.