Remarks on the identifiability of thurstonian paired comparison models under multiple judgment

It is well-known that the representations of the Thurstonian models for difference judgment data are not unique. It has been shown that equivalence classes can be formed to provide a more meaningful partition of the covariance structures of the Thurstonian ranking models. In this paper, we examine the equivalence relations between Thurstonian covariance structure models for paired comparison data obtained under multiple judgment and discuss their implications on the general identification constraints and methods to check for parameter identifiability in restricted models.The author is indebted to Ulf Böckenholt and Albert Maydeu-Olivares for their significant comments and suggestions which led to considerable improvement in this article.     

General self-efficacy,dental anxiety and multiple fears among 20-year-olds in Norway

This paper examines the extent to which low general self-efficacy and painful dental and medical experiences are related to dental anxiety, multiple fears and to avoidance of dental care. A total of 754 20-year-olds completed a series of questionnaires, including the General Self-efficacy Scale (GSE), Geer Fear Scale (GFS) and Dental Fear Survey (DFS). Females had lower self-efficacy, higher dental anxiety and higher scores on the GFS than males. Multivariate analyses (linear stepwise regression) indicated that painful dental experiences, a high score on the GFS and negative opinions about own dental health explained 37% of the variance in DFS scores. Self-efficacy had no predictive power for dental anxiety, and only dental anxiety had predictive power for dental avoidance behavior. Thirty-eight percent of the total variance in GFS scores was explained by the following variables: being a female, high dental anxiety (DFS), low general self-efficacy (GSE) and low educational level of the mother.     

Reducing indices of unhappiness among individuals with profound multiple disabilities during therapeutic exercise routines.

A program was developed to reduce indices of unhappiness that accompanied therapeutic exercise routines among people with profound multiple disabilities. Indices of unhappiness were recorded, using an observation system that had been validated through previous research involving happiness-related variables, while support personnel conducted exercises with 3 participants. A multicomponent program was then implemented that involved presenting highly preferred stimuli before, during, and after each exercise session. Results indicated that the program was accompanied by reduced indices of unhappiness for each participant relative to the traditional method of conducting the exercises, although changes in the preferred stimuli used with 1 participant were required before consistent reductions occurred. Results are discussed regarding the importance of reducing unhappiness indices as a means of enhancing aspects of the daily quality of life for people with profound multiple disabilities. Areas for future research are also discussed, focusing on expanding the unhappiness-reduction procedures to other routine events that may occasion indices of unhappiness.     

Learning to Make Selection and Detection Decisions: The Roles of Base Rate and Feedback

The effects of type of feedback and base rate on threshold learning in a multiple‐cue decision task were examined. In most such decision experiments, participants receive feedback after every trial (full feedback), and a single base rate (usually 0.5) is used. Our experiment explored conditional feedback (feedback only after positive decisions) representing common selection and detection tasks (such as hiring), where the decision maker receives no feedback unless the decision is positive (e.g., hire the applicant). We used three base rates (0.2, 0.5, and 0.8). As expected, performance was best in full feedback, but after 300 learning trials, the difference was small. Conditional feedback generally resulted in fewer positive decisions than full feedback, but this difference was not found in the low (0.2) base rate condition. There were interactions between base rates and types of feedback. Results provide partial support for the constructivist encoding hypothesis of Elwin and colleagues. Simulation results suggest that our results may reflect overconfidence when feedback is not given. With respect to rate of learning, when the base rate was 0.2, conditional feedback participants reached approximately the same selection rate but did so more slowly than the full feedback participants. Partial feedback participants learned slower and appeared to be still learning after 500 trials. When the base rate was 0.5 or 0.8, partial feedback was nearly as good as full feedback, but conditional feedback resulted in a systematically lower rate of positive decisions. Copyright © 2011 John Wiley & Sons, Ltd.     

Relational learning in a context of transposition: a review

In a typical transposition task, an animal is presented with a single pair of stimuli (for example, S3+ S4−, where plus and minus denote reward and nonreward and digits denote stimulus location on a sensory dimension such as size). Subsequently, an animal is presented with a testing pair that contains a previously reinforced or nonreinforced stimulus and a novel stimulus (for example, S2–S3 and S4–S5). Does the choice of a novel S2 instead of previously reinforced S3 in a testing pair S2–S3 indicate that the animal has learned a relation (i.e., “select smaller”)? This review of empirical evidence and theoretical accounts shows that an organism''s behavior in a transposition task is undoubtedly influenced by prior reinforcement history of the training stimuli (Spence, 1937). However, it is also affected by two other factors that are relational in nature—a similarity of two testing stimuli to each other and an overall similarity of the testing pair as a whole to the training pair as a whole. The influence of the two latter factors is especially evident in studies that use multiple pairs of training stimuli and a wide range of testing pairs comprising nonadjacent stimuli (Lazareva, Miner, Young, & Wasserman, 2008; Lazareva, Wasserman, & Young, 2005). In sum, the evidence suggests that both prior reinforcement history and relational information affect an animal''s behavior in a typical transposition task.     

EFFECTS OF A SIGNALED DELAY TO REINFORCEMENT IN THE PREVIOUS AND UPCOMING RATIOS ON BETWEEN-RATIO PAUSING IN FIXED-RATIO SCHEDULES

Domestic hens responded under multiple fixed‐ratio fixed‐ratio schedules with equal fixed ratios. One component provided immediate reinforcement and the other provided reinforcement after a delay, signaled by the offset of the key light. The components were presented quasirandomly so that all four possible transitions occurred in each session. The delay was varied over 0, 4, 8, 16, and 32 s with fixed‐ratio 5 schedules, and over 0, 8 and 32 s with fixed‐ratio 1, 15 and 40 schedules. Main effects of fixed‐ratio value and delay duration were detected on between‐ratio pauses. Pauses were longer when the multiple‐schedule stimulus correlated with a delayed‐reinforcer component was presented, with the longest pauses occurring at the transition from a component with an immediate reinforcer to one with a delayed reinforcer. Pause durations were shortest during immediate components. Overall, both the presence or absence of a delay in the upcoming component, and the presence or absence of a delay in the preceding component affected pause length, but the upcoming delay had the larger effect. Thus changes in delay had similar effects to past reports of the effects of changes in response force, response requirement, and reinforcer magnitude in multiple fixed‐ratio fixed‐ratio schedules.     

Multilevel Reliability Measures of Latent Scores Within an Item Response Theory Framework

Abstract

This paper evaluated multilevel reliability measures in two-level nested designs (e.g., students nested within teachers) within an item response theory framework. A simulation study was implemented to investigate the behavior of the multilevel reliability measures and the uncertainty associated with the measures in various multilevel designs regarding the number of clusters, cluster sizes, and intraclass correlations (ICCs), and in different test lengths, for two parameterizations of multilevel item response models with separate item discriminations or the same item discrimination over levels. Marginal maximum likelihood estimation (MMLE)-multiple imputation and Bayesian analysis were employed to evaluate the accuracy of the multilevel reliability measures and the empirical coverage rates of Monte Carlo (MC) confidence or credible intervals. Considering the accuracy of the multilevel reliability measures and the empirical coverage rate of the intervals, the results lead us to generally recommend MMLE-multiple imputation. In the model with separate item discriminations over levels, marginally acceptable accuracy of the multilevel reliability measures and empirical coverage rate of the MC confidence intervals were found in a limited condition, 200 clusters, 30 cluster size, .2 ICC, and 40 items, in MMLE-multiple imputation. In the model with the same item discrimination over levels, the accuracy of the multilevel reliability measures and the empirical coverage rate of the MC confidence intervals were acceptable in all multilevel designs we considered with 40 items under MMLE-multiple imputation. We discuss these findings and provide guidelines for reporting multilevel reliability measures.     

Asymptotic Standard Errors of Generalized Partial Credit Model True Score Equating Using Characteristic Curve Methods

In this study, the delta method was applied to estimate the standard errors of the true score equating when using the characteristic curve methods with the generalized partial credit model in test equating under the context of the common-item nonequivalent groups equating design. Simulation studies were further conducted to compare the performance of the delta method with that of the bootstrap method and the multiple imputation method. The results indicated that the standard errors produced by the delta method were very close to the criterion empirical standard errors as well as those yielded by the bootstrap method and the multiple imputation method under all the manipulated conditions.     

A Fuzzy Goal Programming Formulation with Multiple Target Levels

The essential activity of a manager is decision making, which is becoming more and more complex, mainly in the multi‐criteria problems. Multi‐choice goal programming (MCGP) is considered as a robust tool in operational research to solve this type of problem. However, in real world problems, determining precise targets for the goals is a difficult task. To deal with such situation, Tabrizi introduced and used in 2012 the concept of membership functions in the MCGP model in order to model the targets fuzziness of each goal. In their model, they considered just only one type of functions (triangular form), which does not reflect adequately the decision maker's preferences that are considered as an essential element for modelling the goal's fuzziness. Their model is called Fuzzy MCGP. In this paper, new ideas are presented to reformulate MCGP model to tackle all types of functions by introducing the (decision maker's) preferences. The concept of indifference thresholds is used in the new formulation for characterizing the imprecision and the preferences associated with all types of the goals. The proposed formulation provides useful insight about the solution of a new class of problems. A numerical example is given to demonstrate the validity and strength of the new formulation. Copyright © 2013 John Wiley & Sons, Ltd.     

认知诊断缺失数据处理方法的比较：零替换、多重插补与极大似然估计法

数据缺失在测验中经常发生, 认知诊断评估也不例外, 数据缺失会导致诊断结果的偏差。首先, 通过模拟研究在多种实验条件下比较了常用的缺失数据处理方法。结果表明：(1)缺失数据导致估计精确性下降, 随着人数与题目数量减少、缺失率增大、题目质量降低, 所有方法的PCCR均下降, Bias绝对值和RMSE均上升。(2)估计题目参数时, EM法表现最好, 其次是MI, FIML和ZR法表现不稳定。(3)估计被试知识状态时, EM和FIML表现最好, MI和ZR表现不稳定。其次, 在PISA2015实证数据中进一步探索了不同方法的表现。综合模拟和实证研究结果, 推荐选用EM或FIML法进行缺失数据处理。