Updates

Part-Whole.bib

@@ -259,6 +259,52 @@ @inproceedings{heerCrowdsourcingGraphicalPerception2010
   file = {/Users/cbbcbail/Zotero/storage/5BZXXU5W/Heer and Bostock - 2010 - Crowdsourcing graphical perception using mechanic.pdf}
 }
 
+@article{hollandsBiasProportionJudgments2000,
+  title = {Bias in {{Proportion Judgments}}: {{The Cyclical Power Model}}},
+  shorttitle = {Bias in {{Proportion Judgments}}},
+  author = {Hollands, Justin and Dyre, Brian},
+  year = {2000},
+  month = jul,
+  journal = {Psychological Review},
+  volume = {107},
+  pages = {500--524},
+  doi = {10.1037/0033-295X.107.3.500},
+  abstract = {When participants make part--whole proportion judgments, systematic bias is commonly observed. In some studies, small proportions are overestimated and large proportions underestimated; in other studies, the reverse pattern occurs. Sometimes the bias pattern repeats cyclically with a higher frequency (e.g., overestimation of proportions less than .25 and between .5 and .75; underestimation otherwise). To account for the various bias patterns, a cyclical power model was derived from Stevens' power law. The model proposes that the amplitude of the bias pattern is determined by the Stevens exponent, {$\beta$} (i.e., the stimulus continuum being judged), and that the frequency of the pattern is determined by a choice of intermediate reference points in the stimulus. When {$\beta$} {$<$} 1, an over-then-under pattern is predicted; when {$\beta$} {$>$} 1, the under-then-over pattern is predicted. Two experiments confirming the model's assumptions are described. A mixed-cycle version of the model is also proposed that predicts observed asymmetries in bias patterns when the set of reference points varies across trials.},
+  file = {/Users/cbbcbail/Zotero/storage/SZP3E6IQ/Hollands and Dyre - 2000 - Bias in Proportion Judgments The Cyclical Power M.pdf}
+}
+
+@article{hollandsJudgingProportionGraphs1998,
+  title = {Judging {{Proportion}} with {{Graphs}}: {{The Summation Model}}},
+  shorttitle = {Judging {{Proportion}} with {{Graphs}}},
+  author = {Hollands, Justin and Spence, Ian},
+  year = {1998},
+  month = apr,
+  journal = {Applied Cognitive Psychology},
+  volume = {12},
+  pages = {173--190},
+  doi = {10.1002/(SICI)1099-0720(199804)12:23.0.CO;2-K},
+  abstract = {People take longer to judge part-to-whole relationships with bar graphs than with pie charts or divided bar graphs. Subjects may perform summation operations to establish the whole with bar graphs, which would be unnecessary for other graph types depicting the whole with a single object. To test this summation model, the number of components forming the whole was varied with bars, divided bars, reference bars, and pies in three experiments. Response time increased with the number of components for bar graphs but there was little increase for other graph types in Experiment 1. An accuracy emphasis in Experiment 2 produced generally longer response times, but had little e€ect on the time per summation. The summation operation was not used when graphs were displayed brie{\textasciimacron}y in Experiment 3, although subjects still took longer with bars. The estimated time for a summation operation is consistent with estimates derived from other research. In general, the bar graph is not e€ective for proportion judgments, and its disadvantage becomes potentially greater as the number of components increases.},
+  file = {/Users/cbbcbail/Zotero/storage/N4NEJFUB/Hollands and Spence - 1998 - Judging Proportion with Graphs The Summation Mode.pdf}
+}
+
+@article{hollandsJudgmentsChangeProportion1992,
+  title = {Judgments of {{Change}} and {{Proportion}} in {{Graphical Perception}}},
+  author = {Hollands, J. G. and Spence, Ian},
+  year = {1992},
+  month = jun,
+  journal = {Human Factors},
+  volume = {34},
+  number = {3},
+  pages = {313--334},
+  publisher = {SAGE Publications Inc},
+  issn = {0018-7208},
+  doi = {10.1177/001872089203400306},
+  urldate = {2024-03-18},
+  abstract = {Subjects judged change and proportion when viewing graphs in two experiments. Change was judged more quickly and accurately with line and bar graphs than with pie charts or tiered bar graphs, and this difference was larger when the rate of change was smaller. Without a graduated scale, proportion was judged more quickly and accurately with pie charts and divided bar graphs than with line or bar graphs. Perception is direct when it requires simpler or fewer mental operations; we propose that perception of change is direct with line and bar graphs, whereas perception of proportion is direct with pie charts and divided bar graphs. The results are also consistent with the proximity compatibility principle. Suggestions for improving the design of graphical displays are given.},
+  langid = {english},
+  file = {/Users/cbbcbail/Zotero/storage/76JDHFGZ/Hollands and Spence - 1992 - Judgments of Change and Proportion in Graphical Pe.pdf}
+}
+
 @article{hondaNumberBiasWisdom2022,
   title = {On the Round Number Bias and Wisdom of Crowds in Different Response Formats for Numerical Estimation},
   author = {Honda, Hidehito and Kagawa, Rina and Shirasuna, Masaru},
@@ -573,6 +619,19 @@ @article{spenceNoHumblePie2005
   file = {/Users/cbbcbail/Zotero/storage/N9SLTN7Y/Spence - 2005 - No Humble Pie The Origins and Usage of a Statisti.pdf}
 }
 
+@article{spenceVisualPsychophysicsSimple1990,
+  title = {Visual {{Psychophysics}} of {{Simple Graphical Elements}}},
+  author = {Spence, Ian},
+  year = {1990},
+  month = dec,
+  journal = {Journal of experimental psychology. Human perception and performance},
+  volume = {16},
+  pages = {683--92},
+  doi = {10.1037//0096-1523.16.4.683},
+  abstract = {The accuracy with which graphical elements are judged was assessed in a psychophysical task that parallels the real-life use of graphs. The task is a variant of the Metfessel-Comrey constant-sum method, and an associated model based on Stevens's law is proposed. The stimuli were horizontal and vertical lines, bars, pie and disk slices, cylinders, boxes, and table entries (numbers). Stevens's law exponents were near unity for numbers and 1-dimensional elements but were also close to 1 for elements possessing 2 or 3 apparent dimensions--subjects accommodate extraneous dimensions that do not carry variation, changing the effective dimensionality of the stimulus. Judgment errors were small, with numbers yielding the best performance; elements such as bars and pie slices were judged almost as accurately; disk elements were judged least accurately, but the magnitude of the errors was not large.},
+  file = {/Users/cbbcbail/Zotero/storage/2EN8GKWJ/Spence - 1990 - Visual Psychophysics of Simple Graphical Elements.pdf}
+}
+
 @inproceedings{suzukiScatterplotBasedVisualizationTool2016,
   title = {A {{Scatterplot-Based Visualization Tool}} for {{Regression Analysis}}},
   booktitle = {2016 20th {{International Conference Information Visualisation}} ({{IV}})},

partWhole.md

@@ -7,8 +7,8 @@ csl: ieee.csl
 
 # Works related to Part-Whole Visualization
 
-## The Relative Merits of Circles and Bars for Representing Component Parts
-### Eells, 1926
+### The Relative Merits of Circles and Bars for Representing Component Parts
+#### Eells, 1926
 
 * The author conducted studies comparing estimation of parts with pie chart and bar chart visualizations. Students in a college course were given a sheet containing a series of pie charts and were asked to label the parts in each chart. The following week they did the same with a sheet of bar charts. Speed is measured by how many charts the student has completed after 5 minutes in the 13 minute experiment. The time spent on pie charts is very similar to bar charts with pie charts being slightly faster. Pie charts were found to outperform bar charts in terms of accuracy where they had smaller error and fewer large errors (greater than 3 points) than bar charts. The author concludes the pie chart is the superior choice for this task contrary to many cited works describing their inferiority without evidence.
 
@@ -76,6 +76,22 @@ csl: ieee.csl
 
 [@spenceDisplayingProportionsPercentages1991a]
 
+### Judgments of Change and Proportion in Graphical Perception
+#### Hollands and Spence, 1992
+
+[@hollandsJudgmentsChangeProportion1992]
+
+
+### Judging Proportion with Graphs: The Summation Model
+#### Hollands and Spence, 1998
+
+[@hollandsJudgingProportionGraphs1998]
+
+### Bias in Proportion Judgments: The Cyclical Power Model
+#### Hollands and Dyer, 2000
+
+[@hollandsBiasProportionJudgments2000]
+
 ### Save the Pies for Dessert
 #### Few, 2007