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Why item response theory should be used for longitudinal questionnaire data analysis in medical research

Overview of attention for article published in BMC Medical Research Methodology, July 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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4 X users

Citations

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58 Dimensions

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99 Mendeley
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1 CiteULike
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Title
Why item response theory should be used for longitudinal questionnaire data analysis in medical research
Published in
BMC Medical Research Methodology, July 2015
DOI 10.1186/s12874-015-0050-x
Pubmed ID
Authors

Rosalie Gorter, Jean-Paul Fox, Jos W. R. Twisk

Abstract

Multi-item questionnaires are important instruments for monitoring health in epidemiological longitudinal studies. Mostly sum-scores are used as a summary measure for these multi-item questionnaires. The objective of this study was to show the negative impact of using sum-score based longitudinal data analysis instead of Item Response Theory (IRT)-based plausible values. In a simulation study (varying the number of items, sample size, and distribution of the outcomes) the parameter estimates resulting from both modeling techniques were compared to the true values. Next, the models were applied to an example dataset from the Amsterdam Growth and Health Longitudinal Study (AGHLS). The results show that using sum-scores leads to overestimation of the within person (repeated measurement) variance and underestimation of the between person variance. We recommend using IRT-based plausible value techniques for analyzing repeatedly measured multi-item questionnaire data.

X Demographics

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The data shown below were collected from the profiles of 4 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 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Netherlands 1 1%
Unknown 97 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 23%
Researcher 16 16%
Student > Master 9 9%
Student > Doctoral Student 8 8%
Professor > Associate Professor 7 7%
Other 19 19%
Unknown 17 17%
Readers by discipline Count As %
Psychology 20 20%
Medicine and Dentistry 18 18%
Social Sciences 15 15%
Computer Science 4 4%
Engineering 4 4%
Other 14 14%
Unknown 24 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 August 2020.
All research outputs
#13,229,066
of 23,313,051 outputs
Outputs from BMC Medical Research Methodology
#1,217
of 2,058 outputs
Outputs of similar age
#117,467
of 264,200 outputs
Outputs of similar age from BMC Medical Research Methodology
#8
of 19 outputs
Altmetric has tracked 23,313,051 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,058 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 39th percentile – i.e., 39% 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 264,200 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.