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Using a standard repeated measures model with arbitrary true score distribution and normal error variables, we present some fundamental closed-form results which explicitly indicate the conditions under which regression effects towards (RTM) and away from the mean are expected. Specifically, we show that for skewed and bimodal distributions many or even most cases will show a regression effect that is in expectation away from the mean, or that is not just towards but actually beyond the mean. We illustrate our results in quantitative detail with typical examples from experimental and biometric applications, which exhibit a clear regression away from the mean (‘egression from the mean’) signature. We aim not to repeal cautionary advice against potential RTM effects, but to present a balanced view of regression effects, based on a clear identification of the conditions governing the form that regression effects take in repeated measures designs.
Most psychological models are intended to describe processes that operate within each individual. In many research areas, however, models are tested by looking at results averaged across many individuals, despite the fact that such averaged results may give a misleading picture of what is true for each one. We consider this conundrum with respect to the interpretation of on-average null effects. Specifically, even though an experimental manipulation might have no effect on average across individuals, it might still have demonstrable effects-albeit in opposite directions-for many or all of the individuals tested. We discuss several examples of research questions for which it would be theoretically crucial to determine whether manipulations really have no effect at the individual level, and we present a method of testing for individual-level effects.
Paradigms used to study the time course of the redundant signals effect (RSE; J. O. Miller, 1986) and temporal order judgments (TOJs) share many important similarities and address related questions concerning the time course of sensory processing. The author of this article proposes and tests a new aggregate diffusion-based model to quantitatively explain both the RSE and TOJs and the relationship between them. Parametric data (13 stimulus onset asynchronies) from an experiment with pairs of visual stimuli (626-nm LEDs) confirm that, relative to central signals (3 degrees), peripheral signals (35 degrees) yield slower reaction times, more strongly modulated RSE time-course functions, and flatter TOJ psychometric functions. All of these qualitative features are well captured, even in quantitative detail, by the aggregate diffusion model.
Dissociations between reaction times and temporal order judgments : a diffusion model approach
(2006)
A diffusion model for simple reaction time (RT) and temporal order judgment (TOJ) tasks was developed to account for a commonly observed dissociation between these 2 tasks: Most stimulus manipulations (e.g., intensity) have larger effects in RT tasks than in TOJ tasks. The model assumes that a detection criterion determines the level of sensory evidence needed to conclude that a stimulus has been presented. Analysis of the performance that would be achieved with different possible criterion settings revealed that performance was optimal with a lower criterion setting for the TOJ task than for the RT task. In addition, the model predicts that effects of stimulus manipulations should increase with the size of the detection criterion. Thus, the model suggests that commonly observed dissociations between RT and TOJ tasks may simply be due to performance optimization in the face of conflicting task demands
Comparing continuous and discrete birthday coincidences : "Same-Day" versus "Within 24 Hours"
(2010)
In its classical form the famous birthday problem (Feller 1968; Mosteller 1987) addresses coincidences within a discrete sample space, looking at births that fall on the same calendar day. However, coincidence phenomena often arise in situations in which it is more natural to consider a continuous-time parameter. We first describe an elementary variant of the classical problem in continuous time, and then derive and illustrate close approximate relations that exist between the discrete and the continuous formulations.
When participants judge the parity of visually presented digits, left-hand responses are faster for numerically small numbers, whereas right-hand responses are faster for large numbers [SNARC effect; S. Dehaene, S. Bossini, P. Giraux, The mental representation of parity and number magnitude. J. Exp. Psychol. Gen., 122, (1993) 371-396]. The present study aimed to find more direct evidence for the functional locus of this effect by recording brain waves while participants performed speeded parity judgments giving manual responses. Our results show clear and robust SNARC effects in the response-locked event-related potentials (ERPs) compared to the stimulus-locked ERPs, confirming that the SNARC effect arises during response-related rather than stimulus-related processing stages. Further analyses of lateralized readiness potentials strongly suggest that the SNARC effect begins to emerge in a response-related stage prior to response preparation and execution, more specifically, in a response selection stage. (c) 2005 Elsevier B.V All rights reserved
Paradigms used to study the time course of the redundant signals effect (RSE; J. O. Miller, 1986) and temporal order judgments (TOJs) share many important similarities and address related questions concerning the time course of sensory processing. The author of this article proposes and tests a new aggregate diffusion-based model to quantitatively explain both the RSE and TOJs and the relationship between them. Parametric data (13 stimulus onset asynchronies) from an experiment with pairs of visual stimuli (626-nm LEDs) confirm that, relative to central signals (3 degrees), peripheral signals (35 degrees) yield slower reaction times, more strongly modulated RSE time-course functions, and flatter TOJ psychometric functions. All of these qualitative features are well captured, even in quantitative detail, by the aggregate diffusion model
Bimanual parity judgments of numerically small (large) digits are faster with the left (right) hand (the SNARC effect; Dehaene, Bossini, & Giraux, 1993). According to one explanation, this effect is culturally derived and reflects ontogenetic influences such as the direction of written language; it might therefore be limited to, or at least be larger with, pairs of lateralized effectors which are instrumental to the production and comprehension of written language. We report two experiments which test for SNARC effects with pedal responses, and compare these effects to manual results. Pedal responses yielded highly systematic SNARC effects; furthermore, these effects did not differ from manual SNARC effects, These results argue against accounts in which the SNARC effect is specific for effectors that are habitually associated with the production or comprehension of written language
Searching for the functional locus of the SNARC effect : evidence for a response-related origin
(2005)
Bimanual parity judgments about numerically small (large) digits are faster with the left (right) hand, even though parity is unrelated to numerical magnitude per se (the SNARC effect; Dehaene, Bossini, & Giraux, 1993). According to one model, this effect reflects a space-related representation of numerical magnitudes (mental number line) with a genuine left-to-right orientation. Alternatively, it may simply reflect an overlearned motor association between numbers and manual responses-as, for example, on typewriters or computer keyboards-in which case it should be weaker or absent with effectors whose horizontal response component is less systematically associated with individual numbers. Two experiments involving comparisons of saccadic and manual parity judgment tasks clearly support the first view; they also establish a vertical SNARC effect, suggesting that our magnitude representation resembles a number map, rather than a number line
Physical size modulates the efficiency of digit comparison, depending on whether the relation of numerical magnitude and physical size is congruent or incongruent (Besner & Coltheart, Neuropsychologia, 17, 467–472, 1979), the number-size congruency effect (NSCE). In addition, Henik and Tzelgov (Memory & Cognition, 10, 389–395, 1982) first reported an NSCE for the reverse task of comparing the physical size of digits such that the numerical magnitude of digits modulated the time required to compare their physical sizes. Does the NSCE in physical comparisons simply reflect a number-mediated bias mechanism related to making decisions and selecting responses about the digit’s sizes? Alternatively, or in addition, the NSCE might indicate a true increase in the ability to discriminate small and large font sizes when these sizes are congruent with the digit’s symbolic numerical meaning, over and above response bias effects. We present a new research design that permits us to apply signal detection theory to a task that required observers to judge the physical size of digits. Our results clearly demonstrate that the NSCE cannot be reduced to mere response bias effects, and that genuine sensitivity gains for congruent number-size pairings contribute to the NSCE.
The number-weight illusion
(2018)
When objects are manually lifted to compare their weight, then smaller objects are judged to be heavier than larger objects of the same physical weights: the classical size-weight illusion (Gregory, 2004). It is also well established that increasing numerical magnitude is strongly associated with increasing physical size: the number-size congruency effect e.g., (Besner & Coltheart Neuropsychologia, 17, 467-472 1979); Henik & Tzelgov Memory & Cognition, 10, 389-395 1982). The present study investigates the question suggested by combining these two classical effects: if smaller numbers are associated with smaller size, and objects of smaller size appear heavier, then are numbered objects (balls) of equal weight and size also judged as heavier when they carry smaller numbers? We present two experiments testing this hypothesis for weight comparisons of numbered (1 to 9) balls of equal size and weight, and report results which largely conform to an interpretation in terms of a new number-weight illusion.
Whereas many cognitive tasks show pronounced aging effects, even in healthy older adults, other tasks seem more resilient to aging. A small number of recent studies suggests that number comparison is possibly one of the abilities that remain unaltered across the life span. We investigated the ability to compare single-digit numbers in young (19-39 years; n = 39) and healthy older (65-79 years; n = 39) adults in considerable detail, analyzing accuracy as well as mean and variance of their response time, together with several other well-established hallmarks of numerical comparison. Using a recent comprehensive process model that parsimoniously accounts quantitatively for many aspects of number comparison (Reike & Schwarz, 2016), we address two fundamental problems in the comparison of older to young adults in numerical comparison tasks: (a) to adequately correct speed measures for different levels of accuracy (older participants were significantly more accurate than young participants), and (b) to distinguish between general sensory and motor slowing on the one hand, as opposed to a specific age-related decline in the efficiency to retrieve and compare numerical magnitude representations. Our results represent strong evidence that healthy older adults compare magnitudes as efficiently as young adults, when the measure of efficiency is uncontaminated by strategic speed-accuracy trade-offs and by sensory and motor stages that are not related to numerical comparison per se. At the same time, older adults aim at a significantly higher accuracy level (risk aversion), which necessarily prolongs processing time, and they also show the well-documented general decline in sensory and/or motor functions.
Following the classical work of Moyer and Landauer (1967), experimental studies investigating the way in which humans process and compare symbolic numerical information regularly used one of two experimental designs. In selection tasks, two numbers are presented, and the task of the participant is to select (for example) the larger one. In classification tasks, a single number is presented, and the participant decides if it is smaller or larger than a predefined standard. Many findings obtained with these paradigms fit in well with the notion of a mental analog representation, or an Approximate Number System (ANS; e.g., Piazza 2010). The ANS is often conceptualized metaphorically as a mental number line, and data from both paradigms are well accounted for by diffusion models based on the stochastic accumulation of noisy partial numerical information over time. The present study investigated a categorization paradigm in which participants decided if a number presented falls into a numerically defined central category. We show that number categorization yields a highly regular, yet considerably more complex pattern of decision times and error rates as compared to the simple monotone relations obtained in traditional selection and classification tasks. We also show that (and how) standard diffusion models of number comparison can be adapted so as to account for mean and standard deviations of all RTs and for error rates in considerable quantitative detail. We conclude that just as traditional number comparison, the more complex process of categorizing numbers conforms well with basic notions of the ANS.
We describe a mathematically simple yet precise model of activation suppression that can explain the negative-going delta plots often observed in standard Simon tasks. The model postulates a race between the identification of the relevant stimulus attribute and the suppression of irrelevant location-based activation, with the irrelevant activation only having an effect if the irrelevant activation is still present at the moment when central processing of the relevant attribute starts. The model can be fitted by maximum likelihood to observed distributions of RTs in congruent and incongruent trials, and it provides good fits to two previously-reported data sets with plausible parameter values. R and MATLAB software for use with the model is provided.