Behavioral momentum in computer-presented discriminations in individuals with severe mental retardation

Behavioral momentum was examined in 2 individuals with severe mental retardation via within-subject manipulations of obtained reinforcer rates. Subjects performed self-paced discrimination problems presented on a touch screen computer monitor. Two different problems, Tasks A and B, alternated in blocks of 15 trials on a multiple schedule. Reinforcers were snack foods. The reinforcement schedule for Task A was continuous (fixed-ratio 1) and the schedule for Task B was continuous in some conditions and variable ratio in other conditions. Behavioral momentum was assessed in test sessions by prefeeding, presenting response-independent food, and making available alternatives to the tasks. When the obtained reinforcer rate for Task A was at least twice that for Task B, resistance to change was greater for Task A. When both reinforcer rates and response rates were a pproximately equal for the two tasks, resistance to change was approximately equal. These results are consistent with behavioral momentum effects. They extend previous findings with humans by examining momentum in self-initiated discrete-trial discrimination tasks with ratio schedules, and by isolating relative reinforcer rates as a controlling variable via within-subject manipulations.     

Response rate viewed as engagement bouts: effects of relative reinforcement and schedule type.

The rate of a reinforced response is conceptualized as a composite of engagement bouts (visits) and responding during visits. Part I of this paper describes a method for estimating the rate of visit initiations and the average number of responses per visit from log survivor plots: the proportion) of interresponse times (IRTs) longer than some elapsed time (log scale) plotted as a function of elapsed time. In Part 2 the method is applied to IRT distributions from rats that obtained food pellets by nose poking a lighted key under various multiple schedules of reinforcement. As expected, total response rate increased as a function of (a) increasing the rate of reinforcement (i.e., variable-interval [VI] 4 min vs. VI 1 mi), (b) increasing the amount of the reinforcer (one food pellet vs. four pellets), (c) increasing the percentage of reinforcers that were contingent on nose poking (25% vs. 100%), and (d) requiring additional responses after the end of the VI schedule (i.e., adding a tandem variable-ratio [VR] 9 requirement). The first three of these variables (relative reinforcement) increased the visit-initiation rate. The tandem VR, in contrast, increased the number of responses per visit. Thus, variables that have similar effects on total response rate can be differentiated based on their effects on the componemts of response rate.     

The general matching law describes choice on concurrent variable-interval schedules of wheel-running reinforcement.

Six male Wistar rats were exposed to concurrent variable-interval schedules of wheel-running reinforcement. The reinforcer associated with each alternative was the opportunity to run for 15 s, and the duration of the changeover delay was 1 s. Results suggested that time allocation was more sensitive to relative reinforcement rate than was response allocation. For time allocation, the mean slopes and intercepts were 0.82 and 0.008, respectively. In contrast, for response allocation, mean slopes and intercepts were 0.60 and 0.03, respectively. Correction for low response rates and high rates of changing over, however, increased slopes for response allocation to about equal those for time allocation. The results of the present study suggest that the two-operant form of the matching law can be extended to wheel-running reinforcement. 'I'he effects of a low overall response rate, a short Changeover delay, and long postreinforcement pausing on the assessment of matching in the present study are discussed.     

工作嵌入的概念、测量及相关变量

工作嵌入代表个体与工作的嵌入程度,用于解释个体为什么留在组织中的一系列因素,具有非情感性、多维度的特点。工作嵌入明显区别于工作满意度、组织承诺等组织行为学变量,包括匹配、联结以及牺牲三个维度。该文明确了工作嵌入与相关变量的概念区别,重点介绍了工作嵌入测量方法的发展以及其在组织行为领域中的研究成果,并指出了今后有必要对其影响因素、测量工具、维度以及结果变量拓展等四个方面进行探讨     

Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods

Composite links and exploded likelihoods are powerful yet simple tools for specifying a wide range of latent variable models. Applications considered include survival or duration models, models for rankings, small area estimation with census information, models for ordinal responses, item response models with guessing, randomized response models, unfolding models, latent class models with random effects, multilevel latent class models, models with log-normal latent variables, and zero-inflated Poisson models with random effects. Some of the ideas are illustrated by estimating an unfolding model for attitudes to female work participation. We wish to thank The Research Council of Norway for a grant supporting our collaboration.     

Multilevel Modeling with Correlated Effects

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized method of moments (GMM) estimation techniques in multilevel modeling, the authors present a series of estimators along a robust to efficient continuum. This continuum depends on the assumptions that the analyst makes regarding the extent of the correlated effects. It is shown that the GMM approach provides an overarching framework that encompasses well-known estimators such as fixed and random effects estimators and also provides more options. These GMM estimators can be expressed as instrumental variable (IV) estimators which enhances their interpretability. Moreover, by exploiting the hierarchical structure of the data, the current technique does not require additional variables unlike traditional IV methods. Further, statistical tests are developed to compare the different estimators. A simulation study examines the finite sample properties of the estimators and tests and confirms the theoretical order of the estimators with respect to their robustness and efficiency. It further shows that not only are regression coefficients biased, but variance components may be severely underestimated in the presence of correlated effects. Empirical standard errors are employed as they are less sensitive to correlated effects when compared to model-based standard errors. An example using student achievement data shows that GMM estimators can be effectively used in a search for the most efficient among unbiased estimators. This research was supported by the National Academy of Education/Spencer Foundation and the National Science Foundation, grant number SES-0436274. We thank the editor, associate editor, and referees for detailed feedback that helped improve the paper.     

A Polychoric Instrumental Variable (PIV) Estimator for Structural Equation Models with Categorical Variables

This paper presents a new polychoric instrumental variable (PIV) estimator to use in structural equation models (SEMs) with categorical observed variables. The PIV estimator is a generalization of Bollen’s (Psychometrika 61:109–121, 1996) 2SLS/IV estimator for continuous variables to categorical endogenous variables. We derive the PIV estimator and its asymptotic standard errors for the regression coefficients in the latent variable and measurement models. We also provide an estimator of the variance and covariance parameters of the model, asymptotic standard errors for these, and test statistics of overall model fit. We examine this estimator via an empirical study and also via a small simulation study. Our results illustrate the greater robustness of the PIV estimator to structural misspecifications than the system-wide estimators that are commonly applied in SEMs. Kenneth Bollen gratefully acknowledges support from NSF SES 0617276, NIDA 1-RO1-DA13148-01, and DA013148-05A2. Albert Maydeu-Olivares was supported by the Department of Universities, Research and Information Society (DURSI) of the Catalan Government, and by grant BSO2003-08507 from the Spanish Ministry of Science and Technology. We thank Sharon Christ, John Hipp, and Shawn Bauldry for research assistance. The comments of the members of the Carolina Structural Equation Modeling (CSEM) group are greatly appreciated. An earlier version of this paper under a different title was presented by K. Bollen at the Psychometric Society Meetings, June, 2002, Chapel Hill, North Carolina.     

The social epidemiologic concept of fundamental cause

The goal of research in social epidemiology is not simply conceptual clarification or theoretical understanding, but more importantly it is to contribute to, and enhance the health of populations (and so, too, the people who constitute those populations). Undoubtedly, understanding how various individual risk factors such as smoking and obesity affect the health of people does contribute to this goal. However, what is distinctive of much on-going work in social epidemiology is the view that analyses making use of individual-level variables is not enough. In the spirit of Durkheim and Weber, S. Leonard Syme makes this point by writing that just “as bad water and food may be harmful to our health, unhealthful forces in our society may be detrimental to our capacity to make choices and to form opinions” conducive to health and well-being. Advocates of upstream (distal) causes of adverse health outcomes propose to identify the most important of these “unhealthful forces” as the fundamental causes of adverse health outcomes. However, without a clear, theoretically precise and well-grounded understanding of the characteristics of fundamental causes, there is little hope in applying the statistical tools of the health sciences to hypotheses about fundamental causes, their outcomes, and policies intended to enhance the health of populations. This paper begins the process of characterizing the social epidemiological concept of fundamental cause in a theoretically respectable and robust way.

时间变量对大学新生人格特质的影响

以台湾地区某大学新生,从1998至2003共六届3141人为对象,分析人格改变情形,统计结果发现13项人格特质的赖氏人格量表中达显著差异的有6项,包括社会外向、攻击性、变异性、神经质、自卑感及虚伪性。性别分析达显著差异的共7项,包括活动性、客观性、协调性、攻击性、变异性、自卑感及神经质;男学生显著高于女学生的有活动性及攻击性,女学生显著高于男学生的有客观性、协调性、变异性、自卑感及神经质。结果显示在时间变量中,大学新生的人格的确发生了转变。     

Latent variable models for analyzing children's processing ability

In this paper, we develop a latent processing ability model to analyze the speed of processing ability data. Our approach can not only effectively evaluate the effects of covariates on the latent processing ability, but also estimate the latent trait of each child by calculating its posterior mean. In addition, we derive the correlations structure of latent traits among different age groups. Simulations are conducted to evaluate the performance of our proposed model. The results indicated that the estimation of model parameters is satisfactory overall. The method is evaluated using real data from children aged 4–7 years in Changchun, China.