Central Tendency Bias Research Articles

Reconstructing the recent visual past: Hierarchical knowledge-based effects in visual working memory

This paper presents two experiments that examine the influence of multiple levels of knowledge on visual working memory (VWM). Experiment 1 focused on memory for faces. Faces were selected from continua that were constructed by morphing two face photographs in 100 steps; half of the continua morphed a famous face into an unfamiliar one, while the other half used two unfamiliar faces. Participants studied six sequentially presented faces each from a different continuum, and at test they had to locate one of these within its continuum. Experiment 2 examined immediate memory for object sizes. On each trial, six images were shown; these were either all vegetables or all random shapes. Immediately after each list, one item was presented again, in a new random size, and participants reproduced its studied size. Results suggested that two levels of knowledge influenced VWM. First, there was an overall central-tendency bias whereby items were remembered as being closer to the overall average or central tokens (averaged across items and trials) than they actually were. Second, when object knowledge was available for the to-be-remembered items (i.e., famous face or typical size of a vegetable) a further bias was introduced in responses. The results extend the findings of Hemmer and Steyvers (Psychonomic Bulletin & Review, 16, 80–87, 2009a) from episodic memory to VWM and contribute to the growing literature which illustrates the complexity and flexibility of the representations subtending VWM performance (e.g., Bae, Olkkonen, Allred, & Flombaum, Journal of Experimental Psychology: General, 144(4):744–63, 2015).

Misremembering emotion: Inductive category effects for complex emotional stimuli.

Memories of objects are biased toward what is typical of the category to which they belong. Prior research on memory for emotional facial expressions has demonstrated a bias towards an emotional expression prototype (e.g., slightly happy faces are remembered as happier). We investigate an alternate source of bias in memory for emotional expressions - the central tendency bias. The central tendency bias skews reconstruction of a memory trace towards the center of the distribution for a particular attribute. This bias has been attributed to a Bayesian combination of an imprecise memory for a particular object with prior information about its category. Until now, studies examining the central tendency bias have focused on simple stimuli. We extend this work to socially relevant, complex, emotional facial expressions. We morphed facial expressions on a continuum from sad to happy. Different ranges of emotion were used in four experiments in which participants viewed individual expressions and, after a variable delay, reproduced each face by adjusting a morph to match it. Estimates were biased toward the center of the presented stimulus range, and the bias increased at longer memory delays, consistent with the Bayesian prediction that as trace memory loses precision, category knowledge is given more weight. The central tendency effect persisted within and across emotion categories (sad, neutral, and happy). This article expands the scope of work oninductive category effects to memory for complex, emotional stimuli.

Benchmarking sensors in smart environments – Method and use cases

Smart environment applications can be based on a large variety of different sensors that may support the same use case, but have specific advantages or disadvantages. Benchmarking can allow determining the most suitable sensor systems for a given application by calculating a single benchmarking score, based on weighted evaluation of features that are relevant in smart environments. This set of features has to represent the complexity of applications in smart environments. In this work we present a benchmarking model that can calculate a benchmarking score, based on nine selected features that cover aspects of performance, the environment and the pervasiveness of the application. Extensions are presented that normalize the benchmark-ing score if required and compensate central tendency bias, if necessary. We outline how this model is applied to capacitive proximity sensors that measure properties of conductive objects over a distance. The model is used to identify existing and find potential new application domains for this upcoming technology in smart environments.

Gender bias favors female nursing students in the written examination evaluation: Crossover study

BackgroundGender discrimination against male nursing students has been reported and attributed to the female-dominated tradition of nursing profession. ObjectivesTo investigate gender bias in the written examination evaluation of undergraduate nursing students. DesignOne-group crossover study with two phases. Setting and ParticipantsFour male and four female examiners provided 400 previously graded examination scripts (50 each) of nursing students. MethodsParticipating examiners were asked to re-grade scripts after any information about student identity was covered to allow blind marking. Script degrees after non-blind and blind marking were compared within male and within female students, as well as between male and female students. ResultsSignificantly more female students' degrees shifted downwards and less of them shifted upwards compared with male students' degrees after blind marking, while mean degree of female students was significantly lower. Among male examiners, significantly more female students' degrees shifted downwards and less of them shifted upwards compared with male students' degrees after blind marking, while mean degree of male students was significantly higher. Among female examiners, mean degree of both male and female students was significantly lower after blind marking. No central tendency bias was detected. ConclusionsGender bias in favor of females was detected in the written examination evaluation of nursing students. This unequal treatment may prevent retention of males in nursing studies and profession.

Working memory and spatial judgments: Cognitive load increases the central tendency bias.

Previous work demonstrates that memory for simple stimuli can be biased by information about the distribution of which the stimulus is a member. Specifically, people underestimate values greater than the distribution's average and overestimate values smaller than the average. This is referred to as the central tendency bias. This bias has been explained as an optimal use of both noisy sensory information and category information. In largely separate literature, cognitive load (CL) experiments attempt to manipulate the available working memory of participants in order to observe the effect on choice or judgments. In two experiments, we demonstrate that participants under high cognitive load exhibit a stronger central tendency bias than when under a low cognitive load. Although not anticipated at the outset, we also find that judgments exhibit an anchoring bias not described previously.

Application and validation of capacitive proximity sensing systems in smart environments

Smart environments feature a number of computing and sensing devices that support occupants in performing their tasks. In the last decades there has been a multitude of advances in miniaturizing sensors and computers, while greatly increasing their performance. As a result new devices are introduced into our daily lives that have a plethora of functions. Gathering information about the occupants is fundamental in adapting the smart environment according to preference and situation. There is a large number of different sensing devices available that can provide information about the user. They include cameras, accelerometers, GPS, acoustic systems, or capacitive sensors. The latter use the properties of an electric field to sense presence and properties of conductive objects within range. They are commonly employed in finger-controlled touch screens that are present in billions of devices. A less common variety is the capacitive proximity sensor. It can detect the presence of the human body over a distance, providing interesting applications in smart environments. Choosing the right sensor technology is an important decision in designing a smart environment application. Apart from looking at previous use cases, this process can be supported by providing more formal methods. In this work I present a benchmarking model that is designed to support this decision process for applications in smart environments. Previous benchmarks for pervasive systems have been adapted towards sensors systems and include metrics that are specific for smart environments. Based on distinct sensor characteristics, different ratings are used as weighting factors in calculating a benchmarking score. The method is verified using popularity matching in two scientific databases. Additionally, there are extensions to cope with central tendency bias and normalization with regards to average feature rating. Four relevant application areas are identified by applying this benchmark to applications in smart environments and capacitive proximity sensors. They are indoor localization, smart appliances, physiological sensing and gesture interaction. Any application area has a set of challenges regarding the required sensor technology, layout of the systems, and processing that can be tackled using various new or improved methods. I will present a collection of existing and novel methods that support processing data generated by capacitive proximity sensors. These are in the areas of sparsely distributed sensors, model-driven fitting methods, heterogeneous sensor systems, image-based processing and physiological signal processing. To evaluate the feasibility of these methods, several prototypes have been created and tested for performance and usability. Six of them are presented in detail. Based on these evaluations and the knowledge generated in the design process, I am able to classify capacitive proximity sensing in smart environments. This classification consists of a comparison to other popular sensing technologies in smart environments, the major benefits of capacitive proximity sensors, and their limitations. In order to support parties interested in developing smart environment applications using capacitive proximity sensors, I present a set of guidelines that support the decision process from technology selection to choice of processing methods.

The central tendency bias in color perception: Effects of internal and external noise

Perceptual estimates can be biased by previously seen stimuli in delayed estimation tasks. These biases are often toward the mean of the whole stimulus set. Recently, we demonstrated such a central tendency bias in delayed color estimation. In the Bayesian framework of perceptual inference, perceptual biases arise when noisy sensory measurements are combined with prior information about the world. Here, we investigate this idea in color perception by manipulating stimulus range and stimulus noise while characterizing delayed color estimates. First, we manipulated the experimental prior for stimulus color by embedding stimuli in collections with different hue ranges. Stimulus range affected hue bias: Hue estimates were always biased toward the mean of the current set. Next, we studied the effect of internal and external noise on the amount of hue bias. Internal noise was manipulated by increasing the delay between the reference and test from 0.4 to 4 s. External noise was manipulated by increasing the amount of chromatic noise in the reference stimulus, while keeping the delay between the reference and test constant at 2 s. Both noise manipulations had a reliable effect on the strength of the central tendency bias. Furthermore, there was a tendency for a positive relationship between variability of the estimates and bias in both noise conditions. In conclusion, observers are able to learn an experimental hue prior, and the weight on the prior can be manipulated by introducing noise in the estimation process.

Estimation of post-test probabilities by residents: Bayesian reasoning versus heuristics?

Although the process of diagnosing invariably begins with a heuristic, we encourage our learners to support their diagnoses by analytical cognitive processes, such as Bayesian reasoning, in an attempt to mitigate the effects of heuristics on diagnosing. There are, however, limited data on the use ± impact of Bayesian reasoning on the accuracy of disease probability estimates. In this study our objective was to explore whether Internal Medicine residents use a Bayesian process to estimate disease probabilities by comparing their disease probability estimates to literature-derived Bayesian post-test probabilities. We gave 35 Internal Medicine residents four clinical vignettes in the form of a referral letter and asked them to estimate the post-test probability of the target condition in each case. We then compared these to literature-derived probabilities. For each vignette the estimated probability was significantly different from the literature-derived probability. For the two cases with low literature-derived probability our participants significantly overestimated the probability of these target conditions being the correct diagnosis, whereas for the two cases with high literature-derived probability the estimated probability was significantly lower than the calculated value. Our results suggest that residents generate inaccurate post-test probability estimates. Possible explanations for this include ineffective application of Bayesian reasoning, attribute substitution whereby a complex cognitive task is replaced by an easier one (e.g., a heuristic), or systematic rater bias, such as central tendency bias. Further studies are needed to identify the reasons for inaccuracy of disease probability estimates and to explore ways of improving accuracy.

SMEs financial risk management assessment in an emerging country: a sad reality of if and cons

This paper extends the results of a previous paper by enlarging the sample used. In this respect, this empirical paper assesses the current state of SMEs financial risk management in an emerging country. Using a descriptive survey as research method, my results document that liquidity and credit are the main financial risks that Romanian SMEs are exposed to. Moreover, Romanian SMEs seems not to be aware of the benefits of having departments of risk management assessment neither risk managers designated or formalised risk management processes. My results indicate also that Romanian SMEs are not aware of the benefits of implementing a holistic risk management approach and the attitude towards risk and uncertainty assessment is more reactive than proactive. As main limitations of my study I could observed both the central tendency bias in the responses gave by my respondents and in some cases social desirability bias. Future research is also approached.

Central Tendency Bias and Self-Reported Risk Attitudes

Central Tendency Bias and Self-Reported Risk Attitudes

Semantic memory for contextual regularities within and across scene categories: Evidence from eye movements

When encountering familiar scenes, observers can use item-specific memory to facilitate the guidance of attention to objects appearing in known locations or configurations. Here, we investigated how memory for relational contingencies that emerge across different scenes can be exploited to guide attention. Participants searched for letter targets embedded in pictures of bedrooms. In a between-subjects manipulation, targets were either always on a bed pillow or randomly positioned. When targets were systematically located within scenes, search for targets became more efficient. Importantly, this learning transferred to bedrooms without pillows, ruling out learning that is based on perceptual contingencies. Learning also transferred to living room scenes, but it did not transfer to kitchen scenes, even though both scene types contained pillows. These results suggest that statistical regularities abstracted across a range of stimuli are governed by semantic expectations regarding the presence of target-predicting local landmarks. Moreover, explicit awareness of these contingencies led to a central tendency bias in recall memory for precise target positions that is similar to the spatial category effects observed in landmark memory. These results broaden the scope of conditions under which contextual cuing operates and demonstrate how semantic memory plays a causal and independent role in the learning of associations between objects in real-world scenes.

Psychology Supervisors' Bias in Evaluations and Letters of Recommendation

ABSTRACT Clinical supervisors have important, but perhaps poorly understood, roles involving quality assessment and improvement, and datekeeping. Supervisors provide evaluation and certification of trainees attesting to their qualifications to continue in their training and performance as mental health service providers. However, bias in supervisory evaluations is a pervasive problem as a training issue in professional psychology. Supervisors (n = 62) at APA-accredited clinical psychology internships estimated rates of leniency, central tendency, and strictness bias among supervisors in general and their own bias in evaluations and letters of reference. The implications of bias in supervisory evaluation are discussed. Potential steps to limit supervisors' bias and increase accountability are recommended.

The reliability and validity of normative and ipsative approaches in the measurement of personality

Ipsative questionnaires of personality have been attacked as necessarily inferior to normative approaches. Some even go so far as to accuse the authors of ipsative scales of reporting spurious statistics and of ‘cheating at patience'. Despite previous papers which claim to demonstrate that ipsative scales overestimate reliabilities, cannot be factored soundly and yield uninterpretable validity coefficients, this investigation shows with synthetic data that these generalizations are ill‐advised. The results demonstrate with simulated data that ipsative scores can be factored soundly, that reliability data are not overestimated, and that under moderate conditions of central tendency bias in normative items, ipsative scores actually correlate better with hypothetical ‘true’ scores than the normative form. When replicated on real data from a sample of 243 subjects, a high correlation was found between ipsative and normative scale scores, ipsative scaling did not produce spuriously high reliabilities, and both normative and ipsative data showed sensible and significant correlations with external rating criteria.

Gradual Specification of Response Amplitude in Human Tracking Performance

These experiments examine how human subjects use information from a target to trigger a response and to specify its trajectory. We first determined if response initiation is predicated on the prior specification of response amplitude by examining the latencies and trajectories of impulses of isometric elbow flexion aimed to one of three visual targets. We varied target predictability (simple versus choice), the urgency with which the response was required, and the level of practice. With practice, subjects could respond to unpredictable targets with the same latency as to predictable ones; the range of response amplitudes was, however, always constricted. This central tendency bias disappeared when subjects were allowed long latencies to respond to the target, suggesting that with urgency, subjects can respond before specification is complete. To determine the time course of specification, the subjects were trained to initiate force impulses in synchrony with the last of a series of predictable tones. They also attempted to match the amplitude of their force impulses to one of three unpredictable visual targets presented at randomly varying times (50-400 ms) prior to the synchronizing tone. At the shortest stimulus-response intervals, before target information could be processed, the amplitudes of responses to all targets were clustered around that of the middle-sized target. Then, as the stimulus-response interval increased, response amplitudes gradually converged upon their specific targets. Specification started at stimulus-response intervals of about 100 ms and extended until about 350 ms.(ABSTRACT TRUNCATED AT 250 WORDS)

Trajectory control in targeted force impulses. IV. Influences of choice, prior experience and urgency.

The present study examines the influences of target predictability, level of practice and response urgency upon the latency and trajectory of a simple motor response. This response is an impulse of isometric force produced by the index finger and aimed to match a step change in a visual target. As expected (Welford 1980), the responses of naive subjects responding as soon as possible after target presentation were initiated at longer latencies when the target steps were of unpredictable amplitudes (choice condition) than when their amplitudes were all the same (simple condition). This choice effect on response latency diminished progressively with practice and eventually disappeared. The trajectories of urgently produced choice responses, however, differed from those of simple responses, and this difference was not reduced by practice. Choice trajectories were more variable and showed a systematic distortion in scaling: response amplitudes exhibited a central tendency bias, or range effect. When targets were equiprobable, responses were biased towards the middle sized target while responses aimed at targets of unequal probability were biased towards the most probable. This effect was independent of the absolute amplitudes of the responses required and was not associated with deviations from the pulse height control policy (Gordon and Ghez 1987a) that human subjects use to vary the amplitude of force impulses. The distortion in scaling and the increased variability of responses aimed at individual targets were markedly reduced when urgency was relaxed and subjects could respond when ready. Then, both simple and choice responses were proportionally scaled to the target, but choice responses were initiated at longer latencies. The changes in trajectory of urgent responses suggests that their inaccuracy occurs because the subjects initiate their responses before the specification of amplitude is complete. The central tendency bias of such incompletely specified responses suggests further that, prior to target presentation, subjects prepare a default response reflecting their expectations. This default may then be modified by information obtained from the target in a process that lasts longer than a minimal reaction time.