What Do Biased Estimates Tell Us about Cognitive Processing? Spatial Judgments as Proportion Estimation

Zax, Alexandra; Williams, Katherine; Patalano, Andrea L.; Slusser, Emily; Cordes, Sara; Barth, Hilary

doi:10.1080/15248372.2019.1653297

Cited by 10 publications

(9 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The main purpose of this work is in some ways methodological: we are establishing that inverse s-shapes can be manipulated by precise control of visual information. In future work, we or other researchers can use this method to test Bayesian and other derivations of the inverse-s pattern (e.g., Zax et al, 2019;Hollands & Dyre, 2000;Landy et al, 2018;Petzschner , 2012). Applications of psychophysics to issues of broad social importance are rare, but we believe that in this case, hope is justified.…”

Section: Discussionmentioning

confidence: 99%

“…Previous work has investigated estimations in bounded spaces, including proportions and percentages. For example Gonzalez & Wu (1999), Hollands & Dyre (2000), Varey et al ( 1990 ) , Erlick (1964), Zax et al (2019) have all conducted psychophysical experiments in which participants' responses fall along a similar inverse s-shaped curve (see Figure 1). In traditional psychophysical cases, these analyses were sometimes derived from Steven's law (Spence, 1990;Hollands & Dyre, 2000;Barth & Paladino, 2011).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Scaling Uncertainty in Visual Perception and Estimation Tasks

Schille-Hudson¹,

Landy²

2020

Preprint

View full text Add to dashboard Cite

Demographic perception—the perception of social quantities of geopolitical scale and social significance—has been extensivelystudied in cognitive and political science (Citrin & Sides, 2008; Gilens, 2001; Herda, 2013). Regular patterns of over- and under-estimation emerge. Americans greatly overestimate, for instance, the proportion of citizens that identify as gay or Muslim, while underestimating those that are Christian. While these errors have been attributed to social factors such as fear of specific minorities (Gallagher, 2003; Wong, 2007), other work has suggested that these patterns result from the psychophysics of the perception of proportions (Landy, Guay & Marghetis 2018). A Bayesian formulation suggests that biases in the estimation of both social proportions and simple visual properties result from a common source: ‘hedging’ uncertain information toward a prior. Here we present a novel lab paradigm and two experiments that manipulate uncertainty in a simple (dot estimation) task, verifying the core assumptions of the Bayesian approach.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scaling Uncertainty in Visual Perception and Estimation Tasks

Schille-Hudson¹,

Landy²

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…This pattern has been modeled as an inverse‐S‐shaped or an S‐shaped curve, with a parameter estimate β indexing degree and direction of bias (e.g., Cohen & Blanc‐Goldhammer, 2011; Slusser & Barth, 2017). Interestingly, rather than being specific to NLE, this bias has been found across a wide range of tasks that can be described as involving proportion judgment (see Hollands & Dyre, 2000; Zax et al, 2019; Zhang & Maloney, 2012, for reviews). Additionally, the pattern of bias is sometimes multi‐cyclical, consistent with the use of intermediate reference points to divide a whole into smaller parts (Cohen & Blanc‐Goldhammer, 2011; Slusser & Barth, 2017; Zax et al, 2019).…”

Section: Left Digit Effect In Number Line Estimationmentioning

confidence: 99%

“…Interestingly, rather than being specific to NLE, this bias has been found across a wide range of tasks that can be described as involving proportion judgment (see Hollands & Dyre, 2000; Zax et al, 2019; Zhang & Maloney, 2012, for reviews). Additionally, the pattern of bias is sometimes multi‐cyclical, consistent with the use of intermediate reference points to divide a whole into smaller parts (Cohen & Blanc‐Goldhammer, 2011; Slusser & Barth, 2017; Zax et al, 2019). This proportion judgment bias was, until recently, the primary known source of systematic error on the NLE task.…”

Section: Left Digit Effect In Number Line Estimationmentioning

confidence: 99%

The left digit effect in a complex judgment task: Evaluating hypothetical college applicants

Patalano

Williams

Weeks

et al. 2021

Behavioral Decision Making

Self Cite

View full text Add to dashboard Cite

A left digit effect has been broadly observed across judgment and decision‐making contexts ranging from product evaluation to medical treatment decisions to number line estimation. For example, $3.00 is judged to be a much greater cost than $2.99, and “801” is estimated strikingly too far to the right of “798” on a number line. Although the consequences of the effects for judgment and decision behavior have been documented, the sources of the effects are not well established. The goal of the current work is to extend investigations of the left digit effect to a new complex judgment activity and to assess whether the magnitude of the effect at the individual level can be predicted from performance on a simpler number skills task on which the left digit effect has also recently been observed. In three experiments (N = 434), adults completed a judgment task in which they rated the strength of hypothetical applicants for college admission and a self‐paced number line estimation task. In all experiments, a small or medium left digit effect was found in the college admissions task, and a large effect was found in number line estimation. Individual‐level variation was observed, but there was no relationship between the magnitudes of the effects in the two tasks. These findings provide evidence of a left digit effect in a novel multiattribute judgment task but offer no evidence that such performance can be predicted from a simple number skills task such as number line estimation.

show abstract

“…This bias has been modeled as an S-shaped or an inverse-S-shaped curve, with the direction and degree of bias indicated by a parameter estimate β (e.g., Cohen & Blanc-Goldhammer, 2011 ; Slusser & Barth, 2017 ; but see Siegler et al, 2009 ). The shape of the curve is thought to be the result of imprecision in one’s estimate of individual magnitudes (e.g., Dehaene et al, 2008 ; Siegler & Opfer, 2003 ) and in the relationship of the part to a whole (e.g., estimating 599 as a proportion of 1000; Barth & Paladino, 2011 ; Cohen & Blanc-Goldhammer, 2011 ; Cohen et al, 2018 ; Slusser & Barth, 2013; see also Hollands & Dyre, 2000 ; Zax et al, 2019 ; Zhang & Maloney, 2012 ). The pattern of bias may also be multi-cyclical (e.g., two S-shapes in a row), with the number of cycles thought to depend on the number of reference points, besides the two endpoints, used to perform the task (e.g., using the line’s midpoint of 500 as an additional reference point; Hollands & Dyre, 2000 ; Peeters et al, 2017 ; Slusser et al, 2013 ; Sullivan et al, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

Summary accuracy feedback and the left digit effect in number line estimation

et al. 2022

Self Cite

View full text Add to dashboard Cite

A robust left digit effect arises in number line estimation such that adults’ estimates for numerals with different hundreds place digits but nearly identical magnitudes are systematically different from one another (e.g., 299 is placed too far to the left of 302). In two experiments, we investigate whether brief feedback interventions designed to increase task effort can reduce or eliminate the left digit effect in a self-paced 0–1,000 number line estimation task. Participants were assigned to complete three blocks of 120 trials each where the middle block contained feedback or no feedback. Feedback was in the form of summary accuracy scores (Experiment 1 ; N = 153) or competitive (summary) accuracy scores (Experiment 2 ; N = 145). In both experiments, planned analyses revealed large left digit effects in all blocks regardless of feedback condition. Feedback did not lead to a reduction in the left digit effect in either experiment, but improvements in overall accuracy were observed. We conclude that there are no changes in the left digit effect resulting from either summary accuracy feedback or competitive accuracy feedback. Also reported are exploratory analyses of trial characteristics (e.g., whether 299 is presented before or after 302) and the left digit effect. Supplementary Information The online version contains supplementary material available at 10.3758/s13421-022-01278-2.

show abstract

What Do Biased Estimates Tell Us about Cognitive Processing? Spatial Judgments as Proportion Estimation

Cited by 10 publications

References 66 publications

Scaling Uncertainty in Visual Perception and Estimation Tasks

Scaling Uncertainty in Visual Perception and Estimation Tasks

The left digit effect in a complex judgment task: Evaluating hypothetical college applicants

Summary accuracy feedback and the left digit effect in number line estimation

Contact Info

Product

Resources

About