Age-related changes in deterministic learning from positive versus negative performance feedback

Feedback-based learning declines with age. Because older adults are generally biased toward positive information (“positivity effect”), learning from positive feedback may be less impaired than learning from negative outcomes. The literature documents mixed results, due possibly to variability between studies in task design. In the current series of studies, we investigated the influence of feedback valence on reinforcement learning in young and older adults. We used nonprobabilistic learning tasks, to more systematically study the effects of feedback magnitude, learning of stimulus–response (S–R) versus stimulus–outcome (S–O) associations, and working-memory capacity. In most experiments, older adults benefitted more from positive than negative feedback, but only with large feedback magnitudes. Positivity effects were pronounced for S–O learning, whereas S–R learning correlated with working-memory capacity in both age groups. These results underline the context dependence of positivity effects in learning and suggest that older adults focus on high gains when these are informative for behavior.     

Processing negative numbers by transforming negatives to positive range and by sign shortcut

Numerals are processed by a phylogenetically old analogue magnitude system. Can culturally new negative numerals be processed using this same representation? To find out whether magnitude representation could be used, we contrasted three possible processing mechanisms: an extended magnitude system for both positive and negative numbers, a mirroring mechanism that could transform negative values to the positive range to be processed on the positive magnitude system, and a sign shortcut strategy that can process the signs of numbers independently of the absolute values of numerals. To test these three hypotheses, a comparison task was used and the reaction time pattern, numerical distance, and Spatial-Numerical Association of Response Codes (SNARC) effect was analysed. The results revealed a mirroring process along with a sign shortcut mechanism. The SNARC effect was observed only when positive numbers were compared.     

A Thurstonian Analysis of Preference Change

This paper presents a Thurstonian model for the analysis of preference change. Preferences are expressed in the form of rankings, possibly with ties. A vector-autoregression framework is used to investigate relationships between past and current rankings. It is shown that this approach yields a parsimonious and easily interpretable representation of individual preference differences in time-dependent ranking data. A detailed analysis of the 1992 National Election Study illustrates the proposed approach.     

Identification and Testing of Modes in Beliefs

Characterizing diversity in beliefs is of paramount importance in empirical research on human behavior. In game theory, the focus is on the hypothesis formation. We present a data set with ideal properties for characterizing such diversity. The data consist of hypotheses on the empirical distribution of opponent choices. Using nonparametric techniques, we identify modes in the data corresponding to subpopulations of behavioral types and find the statistical significance of these modes in the underlying population distribution.     

大学生实时距、空时距估计的比较研究

本研究采用2(空时距、实时距)×8(1秒～8秒)的实验设计,以224名大学生为被试,考察了不同类型、不同长度的时距估计特点,结果发现;(1)时距类型在时距估计中存在主效应,在本实验中,1秒～8秒条件下实时距估计比空时距准确;(2)时距长度在时距估计中存在主效应,时距估计所产生的误差随时距长度的增加而增大;(3)时距类型与时距长度之间存在交互作用,对实时距、空时距估计进行曲线估计及预测,发现两类时距估计呈现动态特征,1845052秒之前实时距估计比空时距准确,之后空时距估计比实时距准确,两类时距估计曲线的变化速度也呈交替上升趋势。     

个人目标相关性对非临床抑郁者未来想象的影响

通过两个实验考查了非临床抑郁者未来想象的异常是否受到个人目标相关性的调节。实验1采用未来想象任务, 实验2采用可能性评估范式, 两个实验一致发现, 抑郁倾向者想象未来积极事件的异常, 受到了与个人目标相关性的调节：相对于非抑郁倾向者, 抑郁倾向者对未来与个人目标相关的积极事件的预期减弱, 而对未来与个人目标无关的积极事件的预期则没有表现出异常; 同时还发现, 抑郁倾向者表现出了对未来消极预期的普遍增强, 不受与个人目标相关性的影响。     

Efficient nonparametric approaches for estimating the operating characteristics of discrete item responses

Rationale and the actual procedures of two nonparametric approaches, called Bivariate P.D.F. Approach and Conditional P.D.F. Approach, for estimating the operating characteristic of a discrete item response, or the conditional probability, given latent trait, that the examinee's response be that specific response, are introduced and discussed. These methods are featured by the facts that: (a) estimation is made without assuming any mathematical forms, and (b) it is based upon a relatively small sample of several hundred to a few thousand examinees.Some examples of the results obtained by the Simple Sum Procedure and the Differential Weight Procedure of the Conditional P.D.F. Approach are given, using simulated data. The usefulness of these nonparametric methods is also discussed.This research was mostly supported by the Office of Naval Research (N00014-77-C-0360, N00014-81-C-0569, N00014-87-K-0320, N00014-90-J-1456).     

The absence of numbers to express the amount may affect delay discounting with humans

Human delay discounting is usually studied with experimental protocols that use symbols to express delay and amount. In order to further understand discounting, we evaluated whether the absence of numbers to represent reward amounts affects discount rate in general, and whether the magnitude effect is generalized to nonsymbolic situations in particular. In Experiment 1, human participants were exposed to a delay‐discounting task in which rewards were presented using dots to represent monetary rewards (nonsymbolic); under this condition the magnitude effect did not occur. Nevertheless, the magnitude effect was observed when equivalent reward amounts were presented using numbers (symbolic). Moreover, in estimation tasks, magnitude increments produced underestimation of large amounts. In Experiment 2, participants were exposed only to the nonsymbolic discounting task and were required to estimate reward amounts in each trial. Consistent with Experiment 1, the absence of numbers representing reward amounts produced similar discount rates of small and large rewards. These results suggest that value of nonsymbolic rewards is a nonlinear function of amount and that value attribution depends on perceived difference between the immediate and the delayed nonsymbolic rewards.     

Dealing with Multiple Solutions in Structural Vector Autoregressive Models

Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.     

Estimation of the Coefficient of Variation with Minimum Risk: A Sequential Method for Minimizing Sampling Error and Study Cost

The coefficient of variation is an effect size measure with many potential uses in psychology and related disciplines. We propose a general theory for a sequential estimation of the population coefficient of variation that considers both the sampling error and the study cost, importantly without specific distributional assumptions. Fixed sample size planning methods, commonly used in psychology and related fields, cannot simultaneously minimize both the sampling error and the study cost. The sequential procedure we develop is the first sequential sampling procedure developed for estimating the coefficient of variation. We first present a method of planning a pilot sample size after the research goals are specified by the researcher. Then, after collecting a sample size as large as the estimated pilot sample size, a check is performed to assess whether the conditions necessary to stop the data collection have been satisfied. If not an additional observation is collected and the check is performed again. This process continues, sequentially, until a stopping rule involving a risk function is satisfied. Our method ensures that the sampling error and the study costs are considered simultaneously so that the cost is not higher than necessary for the tolerable sampling error. We also demonstrate a variety of properties of the distribution of the final sample size for five different distributions under a variety of conditions with a Monte Carlo simulation study. In addition, we provide freely available functions via the MBESS package in R to implement the methods discussed.