Evidence map›Paper›PMID 28123371›Full record

ArticleFrontiers in psychology2016

The Impact of Visualizing Nested Sets. An Empirical Study on Tree Diagrams and Unit Squares.

Katharina Böcherer-Linder, Andreas Eichler

Abstract read
In one paragraph

Article in Frontiers in psychology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  7. Natural frequency trees improve diagnostic efficiency in Bayesian reasoning.Advances in health sciences education : theory and practice · 2021
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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

2 authors.

Katharina Böcherer-LinderInstitute of Mathematics Education, University of Education, Freiburg Freiburg, Germany.
Andreas EichlerInstitute of Mathematics, University of Kassel Kassel, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is an ongoing debate, what properties of visualizations increase people's performance when solving Bayesian reasoning tasks. In the discussion of the properties of two visualizations, i.e., the tree diagram and the unit square, we emphasize how both visualizations make relevant subset relations transparent. Actually, the unit square with natural frequencies reveals the subset relation that is essential for the Bayes' rule in a numerical and geometrical way whereas the tree diagram with natural frequencies does it only in a numerical way. Accordingly, in a first experiment with 148 university students, the unit square outperformed the tree diagram when referring to the students' ability to quantify the subset relation that must be applied in Bayes' rule. As hypothesized, in a second experiment with 143 students, the unit square was significantly more effective when the students' performance in tasks based on Bayes' rule was regarded. Our results could inform the debate referring to Bayesian reasoning since we found that the graphical transparency of nested sets could explain these visualizations' effect.

Indexed as

Bayesian reasoningnested setstree diagramunit squarevisualization

Identifiers

PMID28123371
PMCPMC5226638

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LicenceCC BY
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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.