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A simple ratio-based approach for power and sample size determination for 2-group comparison using Rasch models

Overview of attention for article published in BMC Medical Research Methodology, July 2014
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Title
A simple ratio-based approach for power and sample size determination for 2-group comparison using Rasch models
Published in
BMC Medical Research Methodology, July 2014
DOI 10.1186/1471-2288-14-87
Pubmed ID
Authors

Véronique Sébille, Myriam Blanchin, Francis Guillemin, Bruno Falissard, Jean-Benoit Hardouin

Abstract

Despite the widespread use of patient-reported Outcomes (PRO) in clinical studies, their design remains a challenge. Justification of study size is hardly provided, especially when a Rasch model is planned for analysing the data in a 2-group comparison study. The classical sample size formula (CLASSIC) for comparing normally distributed endpoints between two groups has shown to be inadequate in this setting (underestimated study sizes). A correction factor (RATIO) has been proposed to reach an adequate sample size from the CLASSIC when a Rasch model is intended to be used for analysis. The objective was to explore the impact of the parameters used for study design on the RATIO and to identify the most relevant to provide a simple method for sample size determination for Rasch modelling.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 6 21%
Researcher 5 17%
Student > Ph. D. Student 4 14%
Lecturer 2 7%
Student > Bachelor 2 7%
Other 3 10%
Unknown 7 24%
Readers by discipline Count As %
Psychology 5 17%
Medicine and Dentistry 3 10%
Nursing and Health Professions 3 10%
Engineering 2 7%
Social Sciences 2 7%
Other 7 24%
Unknown 7 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 August 2014.
All research outputs
#14,198,017
of 22,758,963 outputs
Outputs from BMC Medical Research Methodology
#1,375
of 2,009 outputs
Outputs of similar age
#119,255
of 227,324 outputs
Outputs of similar age from BMC Medical Research Methodology
#15
of 25 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,009 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 227,324 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.