Behavior of humans in variable-interval schedules of reinforcement

During Phase I, human subjects pressed a button for monetary reinforcement in five variable-interval schedules, each of which specified a different frequency of reinforcement. The rate of responding was an increasing, negatively accelerated function of reinforcement frequency; the data conformed closely to Herrnstein's equation. During Phase II, the same five schedules were in operation, but in addition a concurrent variable-interval schedule (B) was introduced, responses on which were always reinforced at the same frequency. Response rate in component A increased while the response rate in B decreased, as a function of the reinforcement frequency in component A. Relative response rates in the two component schedules matched the relative frequencies of reinforcement. Comparing the absolute response rates in component A during Phase I and Phase II it was found that introduction of the concurrent schedule did not affect the value of the theoretical maximum response rate, but did increase the value of the reinforcement frequency needed to obtain any particular submaximal response rate.     

Obtaining Systematic Teacher Reports of Disruptive Behavior Disorders Utilizing DSM-IV

This study examines the psychometric properties of the Vanderbilt AD/HD Diagnostic Teacher Rating Scale (VADTRS) and provides preliminary normative data from a large, geographically defined population. The VADTRS consists of the complete list of DSM-IV AD/HD symptoms, a screen for other disruptive behavior disorders, anxiety and depression, and ratings of academic and classroom behavior performance. Teachers in one suburban county completed the scale for their students during 2 consecutive years. Statistical methods included (a) exploratory and confirmatory latent variable analyses of item data, (b) evaluation of the internal consistency of the latent dimensions, (c) evaluation of latent structure concordance between school year samples, and (d) preliminary evaluation of criterion-related validity. The instrument comprises four behavioral dimensions and two performance dimensions. The behavioral dimensions were concordant between school years and were consistent with a priori DSM-IV diagnostic criteria. Correlations between latent dimensions and relevant, known disorders or problems varied from .25 to .66.     

Inhibiting function of reinforcement: magnitude effects on variable-interval schedules

In two experiments, the performance of rats under constant-probability and arithmetic variable-interval schedules respectively was compared when the concentration of a liquid reinforcer was varied within sessions; in other sessions, half of the reinforcers were randomly omitted. When the discriminative function of the reinforcer as a signal for a decrease in the probability of reinforcement was attenuated (the constant-probability schedule) the postreinforcement pause duration was nevertheless an increasing function of reinforcer magnitude. This relationship was also present, but more marked, when the temporal discriminative function of the reinforcer was enhanced (the arithmetic schedule). These results suggested that reinforcement has an unconditioned suppressive effect on the reinforced response distinct from any discriminative function it may acquire. The reinforcement-omission effect, where response rate accelerates following omission, was observed when the reinforcer functioned as an effective temporal discriminative stimulus, but not when such temporal control was absent.     

Positive and negative contrast as a function of component duration for key pecking and treadle pressing

Pigeons responded on several multiple schedules for food reinforcers. The duration of the components varied from four seconds to 16 minutes. The absolute size of positive (Experiment 1) and negative (Experiment 2) behavioral contrast varied inversely with component duration when key pecks produced the reinforcers. The absolute size of negative contrast varied directly with component duration, when treadle presses produced the reinforcers (Experiment 3). These results conform to theories that suggest that positive and negative contrast are symmetrical when pigeons peck keys. They also conform to theories that suggest that the same principles do not govern contrast when pigeons peck keys as when they press treadles. Finally, the results support the measurement of behavioral contrast by the differences between baseline rates of responding and the rates emitted when contrast is present.     

Feedback functions for variable-interval reinforcement

On a given variable-interval schedule, the average obtained rate of reinforcement depends on the average rate of responding. An expression for this feedback effect is derived from the assumptions that free-operant responding occurs in bursts with a constant tempo, alternating with periods of engagement in other activities; that the durations of bursts and other activities are exponentially distributed; and that the rates of initiating and terminating bursts are inversely related. The expression provides a satisfactory account of the data of three experiments.     

Variable-time reinforcement schedules in the treatment of socially maintained problem behavior

Noncontingent reinforcement (NCR) consists of delivering a reinforcer on a time-based schedule, independent of responding. Studies evaluating the effectiveness of NCR as treatment for problem behavior have used fixed-time (FT) schedules of reinforcement. In this study, the efficacy of NCR with variable-time (VT) schedules was evaluated by comparing the effects of VT and FT reinforcement schedules with 2 individuals who engaged in problem behavior maintained by positive reinforcement. Both FT and VT schedules were effective in reducing problem behavior. These findings suggest that VT schedules can be used to treat problem behavior maintained by social consequences.     

Q‐sort methodology: Bridging the divide between qualitative and quantitative. An introduction to an innovative method for psychotherapy research

Q‐methodology offers unique opportunities for counselling and psychotherapy researchers and clinicians. It is an innovative technique capable of bridging the divide between clinical knowledge and the quantitative systematisation of it. It was initially developed by Stephenson as a data collection and data analytic method to empirically study human subjectivity. It was then extended by the British School to study shared viewpoints, thereby adopting a multi‐participant design and a highly unusual form of qualitative analysis. Finally, it was adapted by the Californian School for use as a standardised observer‐rated assessment tool. Its attractiveness stems from its aptitude to produce holistic data as it collects both quantitative and narrative data. This paper will provide an introduction to Q‐statistics and Q‐methodology (person‐centred) by contrasting it to R‐statistics and R‐methodology (variable‐centred). It will then provide an overview of the three schools of Q‐methodology and their various merits demonstrated with an example.     

Joint Modeling of Ability and Differential Speed Using Responses and Response Times

With computerized testing, it is possible to record both the responses of test takers to test questions (i.e., items) and the amount of time spent by a test taker in responding to each question. Various models have been proposed that take into account both test-taker ability and working speed, with the many models assuming a constant working speed throughout the test. The constant working speed assumption may be inappropriate for various reasons. For example, a test taker may need to adjust the pace due to time mismanagement, or a test taker who started out working too fast may reduce the working speed to improve accuracy. A model is proposed here that allows for variable working speed. An illustration of the model using the Amsterdam Chess Test data is provided.     

结构方程建模中的题目打包策略

结构方程建模中题目打包法的优缺点包括：指标数据质量变好、模型拟合程度提高; 估计偏差不大, 可校正; 估计稳定, 但降低了敏感性与可证伪性。打包法的前提条件是单维、同质, 适合结构模型分析, 不适合测量模型分析。对于单维测验, 给出了一个打包流程。对于通常的多个子量表(多维结构)测验, 推荐在子量表内打包, 每个子量表打包成1个指标或者3个指标, 用于结构方程建模。