Further evidence of the invalidity of the magnitude estimation method

IntroductionThe magnitude estimation method is widely applied in diverse areas of psychology. However, Weiss (1972) found that this method may produce judgments that inaccurately represent subjective magnitudes: constructing the stimuli according to a factorial design allowed the bias caused by magnitude estimation to be exposed as a spurious divergence of factorial curves.ObjectiveThe present study experimentally compared magnitude estimation with graphic rating and ratio estimation. The comparison of magnitude estimation with graphic rating retested Weiss's finding. The comparison of magnitude estimation with ratio estimation explored the hypothesis that magnitude estimation may cause a divergence of factorial curves due to the requirement of magnitude estimation to multiply and divide numbers—both ratio estimation and magnitude estimation required participants to judge ratios, but only magnitude estimation required mental multiplication and division.MethodUsing a 3 × 4 factorial experimental design, an achromatic disk was presented concentrically with a larger achromatic square. The brightness of the disk varied with the luminance of the disk and, due to simultaneous contrast, with the luminance of the square. Three different groups of participants judged the brightness of the disk: one group by graphic rating, another by ratio estimation, and the third by magnitude estimation.ResultsIn accord with Weiss's results, graphic rating yielded roughly parallel factorial curves whereas magnitude estimation yielded diverging factorial curves. Ratio estimation also yielded roughly parallel factorial curves, supporting the hypothesis that the magnitude estimation task itself may cause divergence of factorial curves due to the requirement of this method to mentally multiply and divide numbers.ConclusionCaution should be taken in using magnitude estimation, especially in factorial experiments, because this method is likely to cause the researcher to make incorrect inferences about the functional relations between the variables involved in mental information integration. Ratio estimation yields a pattern of factorial curves essentially equivalent to that obtained by graphic rating.     

Random effects and extended generalized partial credit models

In this paper it is shown that under the random effects generalized partial credit model for the measurement of a single latent variable by a set of polytomously scored items, the joint marginal probability distribution of the item scores has a closed-form expression in terms of item category location parameters, parameters that characterize the distribution of the latent variable in the subpopulation of examinees with a zero score on all items, and item-scaling parameters. Due to this closed-form expression, all parameters of the random effects generalized partial credit model can be estimated using marginal maximum likelihood estimation without assuming a particular distribution of the latent variable in the population of examinees and without using numerical integration. Also due to this closed-form expression, new special cases of the random effects generalized partial credit model can be identified. In addition to these new special cases, a slightly more general model than the random effects generalized partial credit model is presented. This slightly more general model is called the extended generalized partial credit model. Attention is paid to maximum likelihood estimation of the parameters of the extended generalized partial credit model and to assessing the goodness of fit of the model using generalized likelihood ratio tests. Attention is also paid to person parameter estimation under the random effects generalized partial credit model. It is shown that expected a posteriori estimates can be obtained for all possible score patterns. A simulation study is carried out to show the usefulness of the proposed models compared to the standard models that assume normality of the latent variable in the population of examinees. In an empirical example, some of the procedures proposed are demonstrated.     

On Judgments of Approximately Equal

Although precision is often important in quantitative judgment, sometimes, it is valuable to recognize that two quantities are roughly the same. Fuzzy‐trace theory suggests that approximately equal judgments rely on gist representations (i.e., meaningful fuzzy categories of quantity). We conducted three experiments to investigate approximately equal judgments with number pairs presented in different formats, both with and without semantic content (breast cancer statistics). In each study, the ratio of the smaller divided by larger number predicted approximately equal judgments. Experiment 1 also examined how knowledge of breast cancer, presentation format (frequencies vs. percentages), and differences in gist comprehension of breast cancer information influence fuzzy equality judgments. As predicted by the fuzzy‐trace theory concept of denominator neglect, approximately equal judgments were more sensitive, as measured by signal detection theory (SDT) analyses, when presented as percentages. In both experiments with breast cancer statistics, people were more likely to judge number pairs approximately equal when they were embedded in sentences about breast cancer, and breast cancer knowledge predicted increased perception of equality, when appropriately consistent with reliable sources, and increased judgment sensitivity. In Experiment 2, a simple intervention focusing on gist meaning increased source‐consistent approximately equal judgments, increased SDT judgment sensitivity, and decreased SDT response bias. In Experiment 3, using number pairs devoid of semantic context spanning four orders of magnitude, we further examined ratio similarity. Overall, more knowledgeable judges and those who better understood the gist of meaningful numbers were more likely to judge literally different numbers as “approximately equal” rather than make precise discriminations that were meaningless. Copyright © 2017 John Wiley & Sons, Ltd.     

Feedback frequency of graphical countdown timers affects pedestrian estimated waiting time at red lights

Graphical countdown timers (similar to a progress bar) have the potential to shorten pedestrians’ perceived waiting time at the red light. Based on the findings from human-computer interaction (HCI) and time estimation theories, the potential may be affected by feedback frequency. This study tested how the feedback frequency of countdown progress bar in traffic light influenced time estimation in a field experiment, and further explored its mechanism in a laboratory experiment. In both experiments, participants estimated various durations (30 s, 45 s, 60 s) under three levels of feedback frequency: low (0.5 Hz), medium (1 Hz), and high (2 Hz). The results showed that although waiting time was underestimated in all conditions, lower feedback frequency led to shorter estimated duration, with slight changes in different contexts. In the traffic context, the effect of feedback frequency was comparable across different countdown duration, but it became stronger at longer countdown duration in the non-traffic context. Overall, the effect of feedback frequency was accompanied by changes in neither arousal level (measured by the subjective scale and physiological indices) nor internal clock speed, which are two critical determinants of time perception. The findings have practical implications on the display design of red light and theoretical implications on time estimation processes.     

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

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.     

二参数逻辑斯蒂模型项目参数的估计精度

项目参数的估计精度对于测验的编制尤其是题库的建立十分重要。目前,国内外对项目参数估计精度的研究,大部分是基于在已知项目参数真值的情况下,运用各种参数估计方法产生新的估计值,再和真值进行偏度(BIAS)和均方根差(RMSE)的比较,从而说明该种估计方法的有效性。但是这种方法不能提供不同的参数真值之间的估计误差的变化规律。为了弥补这一缺陷,本文尝试从项目参数估计信息函数的角度出发研究项目参数的估计精度问题。本研究以二参数Logistic模型作为研究对象,首先定义了项目参数的估计信息函数,然后基于完全随机实验设计,通过模拟研究的方法探索影响项目参数的估计精度的因素,实验共设计了(2×3×2)种情形。研究结果表明：(1)项目参数(a,b)的估计精度均随着被试样本量的增大而提高;(2)被试的能力分布对难度参数的估计精度影响较大,对区分度参数的估计精度影响相对较小;(3)难度参数和区分度参数的估计精度都分别受到参数a和参数b的共同作用。     

Knowledge of Results for Motor Learning: Relationship Between Error Estimation and Knowledge of Results Frequency

The authors of the present study investigated the apparent contradiction between early and more recent views of knowledge of results (KR), the idea that how one is engaged before receiving KR may not be independent of how one uses that KR. In a 2 × 2 factorial design, participants (N = 64) practiced a simple force-production task and (a) were required, or not required, to estimate error about their previous response and (b) were provided KR either after every response (100%) or after every 5th response (20%) during acquisition. A no-KR retention test revealed an interaction between acquisition error estimation and KR frequencies. The group that received 100% KR and was required to error estimate during acquisition performed the best during retention. The 2 groups that received 20% KR performed less well. Finally, the group that received 100% KR and was not required to error estimate during acquisition performed the poorest during retention. One general interpretation of that pattern of results is that motor learning is an increasing function of the degree to which participants use KR to test response hypotheses (J. A. Adams, 1971; R. A. Schmidt, 1975). Practicing simple responses coupled with error estimation may embody response hypotheses that can be tested with KR, thus benefiting motor learning most under a 100% KR condition. Practicing simple responses without error estimation is less likely to embody response hypothesis, however, which may increase the probability that participants will use KR to guide upcoming responses, thus attenuating motor learning under a 100% KR condition. The authors conclude, therefore, that how one is engaged before receiving KR may not be independent of how one uses KR.     

A Bayesian Approach to More Stable Estimates of Group-Level Effects in Contextual Studies

Multilevel analyses are often used to estimate the effects of group-level constructs. However, when using aggregated individual data (e.g., student ratings) to assess a group-level construct (e.g., classroom climate), the observed group mean might not provide a reliable measure of the unobserved latent group mean. In the present article, we propose a Bayesian approach that can be used to estimate a multilevel latent covariate model, which corrects for the unreliable assessment of the latent group mean when estimating the group-level effect. A simulation study was conducted to evaluate the choice of different priors for the group-level variance of the predictor variable and to compare the Bayesian approach with the maximum likelihood approach implemented in the software Mplus. Results showed that, under problematic conditions (i.e., small number of groups, predictor variable with a small ICC), the Bayesian approach produced more accurate estimates of the group-level effect than the maximum likelihood approach did.     

基于GRM模型的BP神经网络参数估计

目前参数估计多采用统计方法,存在耗时长、要求被试样本容量大和项目数多等缺点。本文将BP神经网络和降维法相结合,对GRM的项目参数和考生能力参数进行估计。蒙特卡洛模拟结果显示：（1）不管是人多题少还是题多人少,该网络设计下的参数估计精度都较高;（2）可以应用到多个不同等级评分的参数估计中,甚至是超过15个等级的项目参数,估计精度也较高,这是其他参数估计方法所不可比拟的;（3）运行的时长和统计估计方法相比大大缩减。