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The use of percentage change from baseline as an outcome in a controlled trial is statistically inefficient: a simulation study

Overview of attention for article published in BMC Medical Research Methodology, June 2001
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)

Mentioned by

blogs
1 blog
twitter
32 tweeters
patent
1 patent
q&a
2 Q&A threads

Citations

dimensions_citation
259 Dimensions

Readers on

mendeley
425 Mendeley
citeulike
6 CiteULike
connotea
1 Connotea
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Title
The use of percentage change from baseline as an outcome in a controlled trial is statistically inefficient: a simulation study
Published in
BMC Medical Research Methodology, June 2001
DOI 10.1186/1471-2288-1-6
Pubmed ID
Authors

Andrew J Vickers

Abstract

Many randomized trials involve measuring a continuous outcome - such as pain, body weight or blood pressure - at baseline and after treatment. In this paper, I compare four possibilities for how such trials can be analyzed: post-treatment; change between baseline and post-treatment; percentage change between baseline and post-treatment and analysis of covariance (ANCOVA) with baseline score as a covariate. The statistical power of each method was determined for a hypothetical randomized trial under a range of correlations between baseline and post-treatment scores. ANCOVA has the highest statistical power. Change from baseline has acceptable power when correlation between baseline and post-treatment scores is high;when correlation is low, analyzing only post-treatment scores has reasonable power. Percentage change from baseline has the lowest statistical power and was highly sensitive to changes in variance. Theoretical considerations suggest that percentage change from baseline will also fail to protect from bias in the case of baseline imbalance and will lead to an excess of trials with non-normally distributed outcome data. Percentage change from baseline should not be used in statistical analysis. Trialists wishing to report this statistic should use another method, such as ANCOVA, and convert the results to a percentage change by using mean baseline scores.

Twitter Demographics

The data shown below were collected from the profiles of 32 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 425 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 2%
United Kingdom 8 2%
Spain 5 1%
Germany 3 <1%
Switzerland 3 <1%
Sweden 2 <1%
Australia 2 <1%
Greece 2 <1%
Ireland 2 <1%
Other 9 2%
Unknown 380 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 119 28%
Student > Ph. D. Student 98 23%
Student > Master 37 9%
Professor 36 8%
Professor > Associate Professor 26 6%
Other 84 20%
Unknown 25 6%
Readers by discipline Count As %
Medicine and Dentistry 134 32%
Agricultural and Biological Sciences 50 12%
Psychology 35 8%
Mathematics 26 6%
Neuroscience 21 5%
Other 100 24%
Unknown 59 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 33. 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 February 2020.
All research outputs
#571,858
of 14,460,745 outputs
Outputs from BMC Medical Research Methodology
#71
of 1,333 outputs
Outputs of similar age
#11,743
of 229,480 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 14,460,745 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,333 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has done particularly well, scoring higher than 94% of its peers.
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 229,480 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them