改进的MCMC算法及其在估计IRT模型参数中的应用

本文首先简要的阐述了MCMC算法的思想及在IRT参数估计中的操作过程;其次,针对该算法存在的一些问题,提出相应的改进建议;然后,分别运用传统的和改进型的MCMC算法进行模拟数据分析和比较,结果显示新的方法表现更好;最后总结新方法的优点所在,并指出下一步的研究方向。     

Benchmark‐based strategies in whole number line estimation

In this study, we used verbal protocols to identify whether adults spontaneously apply quartile‐based strategies or whether they need additional external support to use these strategies when solving a 0–1,000 number line estimation (NLE) task. Participants were assigned to one of three conditions based on the number of external benchmarks provided on the number line. In the bounded condition only the origin and endpoint were indicated, the mid‐point condition included an additional external benchmark at 50%, and in the quartile condition three additional external benchmarks at 25%, 50%, and 75% were specified. Firstly, participants in the bounded condition reported to spontaneously apply quartile‐based strategies to calibrate their estimates. Moreover, participants frequently relied on the external benchmarks for creating internal benchmarks at the mid‐point, quartiles, and even octiles of the number line. Secondly, overall estimation accuracy improved as the number of external benchmarks increased, and target numbers close to external benchmarks were estimated more accurately and with less variability. Thirdly, the use of a larger variety in benchmark‐based strategies was positively related to NLE accuracy. In summary, this study provides evidence that the NLE task induces more sophisticated strategy use in participants than initially anticipated.     

Preference and reinforcer efficacy of high‐ and low‐tech items: A comparison of item type and duration of access

This study examined the interactions of stimulus type (high‐ vs. low‐tech) and magnitude (duration of access) on preference and reinforcer efficacy. Two preference assessments were conducted to identify highly preferred high‐tech and low‐tech items for each participant. A subsequent assessment examined preference for those items when provided at 30‐s and 600‐s durations. We then evaluated reinforcer efficacy for those same items when provided for a range of durations using progressive‐ratio schedules. Results suggested item type and access duration interacted to influence preference and reinforcer efficacy. Participants preferred high‐tech items at longer durations of access and engaged in more responding when the high‐tech item was provided for long durations, but these patterns were reversed for the low‐tech item. In addition, participants engaged in less responding when the high‐tech item was provided for short durations and when the low‐tech item was provided for long durations.     

A second type of magnitude effect: Reinforcer magnitude differentiates delay discounting between substance users and controls

Basic research on delay discounting, examining preference for smaller–sooner or larger–later reinforcers, has demonstrated a variety of findings of considerable generality. One of these, the magnitude effect, is the observation that individuals tend to exhibit greater preference for the immediate with smaller magnitude reinforcers. Delay discounting has also proved to be a useful marker of addiction, as demonstrated by the highly replicated finding of greater discounting rates in substance users compared to controls. However, some research on delay discounting rates in substance users, particularly research examining discounting of small‐magnitude reinforcers, has not found significant differences compared to controls. Here, we hypothesize that the magnitude effect could produce ceiling effects at small magnitudes, thus obscuring differences in delay discounting between groups. We examined differences in discounting between high‐risk substance users and controls over a broad range of magnitudes of monetary amounts ($0.10, $1.00, $10.00, $100.00, and $1000.00) in 116 Amazon Mechanical Turk workers. We found no significant differences in discounting rates between users and controls at the smallest reinforcer magnitudes ($0.10 and $1.00) and further found that differences became more pronounced as magnitudes increased. These results provide an understanding of a second form of the magnitude effect: That is, differences in discounting between populations can become more evident as a function of reinforcer magnitude.     

Bayesian Estimation for Item Factor Analysis Models with Sparse Categorical Indicators

Psychometric models for item-level data are broadly useful in psychology. A recurring issue for estimating item factor analysis (IFA) models is low-item endorsement (item sparseness), due to limited sample sizes or extreme items such as rare symptoms or behaviors. In this paper, I demonstrate that under conditions characterized by sparseness, currently available estimation methods, including maximum likelihood (ML), are likely to fail to converge or lead to extreme estimates and low empirical power. Bayesian estimation incorporating prior information is a promising alternative to ML estimation for IFA models with item sparseness. In this article, I use a simulation study to demonstrate that Bayesian estimation incorporating general prior information improves parameter estimate stability, overall variability in estimates, and power for IFA models with sparse, categorical indicators. Importantly, the priors proposed here can be generally applied to many research contexts in psychology, and they do not impact results compared to ML when indicators are not sparse. I then apply this method to examine the relationship between suicide ideation and insomnia in a sample of first-year college students. This provides an important alternative for researchers who may need to model items with sparse endorsement.     

Evaluating a model of global psychophysical judgments—I: Behavioral properties of summations and productions

The research presented is a partial empirical evaluation of the second author's proposed psychophysical theory [Luce (2002). Psychological Review, 109, 520-532; Luce (2004). Psychological Review, 111, 446-454]. The theory deals with the global percept of subjective intensity, in which there is a psychophysical function Ψ that maps pairs of physical intensities onto the positive real numbers and represents, in an explicit mathematical way, subjective summation and a form of ratio production. A number of behavioral properties have been shown to follow from these specific representations, and in the presence of certain plausible background assumptions these properties are also sufficient for the representations. In four auditory experiments, key behavioral properties of summation over the two ears and a form of generalized ratio production are evaluated empirically. Considerable support is reported for particular forms of Ψ for summations and ratio productions separately. A second article, Steingrimsson and Luce (Journal of Mathematical Psychology, in press), explores the behavioral properties that link summations and productions.     

听觉经验缺失对时距估计影响的实验研究

采用复制法,通过聋人与听力正常人时距估计的对比实验研究,结果发现听觉经验缺失对时距估计有一定的影响：（1）两类被试在2000ms和10000ms的时距估计中,再现时距的平均数表现出了显著性差异。听力正常被试倾向于低估时距,聋人被试倾向于高估时距。（2）聋人被试不同时距再现相对误差率之间不存在显著性差异;听力正常被试时距再现相对错误率在2000ms与10000ms、30000ms存在显著差异,10000ms和30000ms之间差异不显著。     

Stevens’ Direct Scaling Methods and the Uniqueness Problem

Stevens postulated that we can use the responses of a participant in a ratio scaling experiment directly to construct a psychophysical function representing the participant's sensations. Although Stevens' methods of constructing measurement scales are widely used in the behavioral sciences, the problem of which scale type is appropriate to describe ratio scaling data is still unresolved. To deal with this problem, we develop a theoretical framework to specify the scale type attained by Stevens' direct scaling methods. It is shown, under fairly mild background assumptions, that the behavioral axioms presented in this paper are necessary and sufficient for the psychophysical functions to be ordinal-, interval-, log-interval-, or ratio-scales. Furthermore, suggestions on how to test these behavioral axioms are provided. Requests for reprints should be sent to thomas.     

主体关联性对贝叶斯推理概率估计的影响

用贝叶斯推理问题为实验材料,探讨了主体关联性对贝叶斯推理概率估计的影响。结果表明,当估计的事件与主体有关时,被试对消极事件概率估计较低,对积极事件概率估计值;当估计的事件与主体无关时,被试对消极事件和积极事件的概率估计无显著差异。反应时分析表明,被试对消极事件的概率估计比对积极事件的概率估计时间显著地长,当消极事件与主体有关时概率估计时间就更长;而对积极事件的概率估计,与主体有关和与主体无关时反应时差异不显著。这表明,被试对消极事件的概率估计(特别是消极事件与己有关时)更为慎重。     

短时距估计中刺激物的动态变化效应

用两个实验考查了时距估计中刺激物的动态变化效应。结果发现,刺激物的运动、速度和旋转角度显著地影响着被试的时间判断,刺激物速度的时距延长效应对于较长时距(18s-24s)来说更加明显;运动刺激与较短、较准确的时距判断相关联;旋转角度的减少使得被试低估时距,而旋转角度的增加使得时距估计呈高估倾向。被试在时间估计过程中表现出长时距低估和短时距高估现象,本研究得到的时间估计转换点是11.4s,此点与先前的有关研究基本一致。