The technical drift of applied behavior analysis

Four dimensions (applied, analytic, general, conceptual) were selected from Baer, Wolf, and Risley's (1968) seminal article on the nature of applied behavior analysis and were monitored throughout the first 10 volumes of the Journal of Applied Behavior Analysis. Each of the experimental articles in Volumes 1 through 6 and the first half of Volumes 7 through 10 was rated on each of these dimensions. The trends showed that applied behavior analysis is becoming a more purely technical effort, with less interest in conceptual questions. We are using simpler experimental designs and are conducting fewer analogue studies. Although concern for maintenance is increasing, other forms of generality are being measured or analyzed less often. These trends are discussed in terms of a technical drift in applied behavior analysis.     

Statistics as psychometrics

In this paper, modern statistics is considered as a branch of psychometrics and the question of how the central problems of statistics can be resolved using psychometric methods is investigated. Theories and methods developed in the fields of test theory, scaling, and factor analysis are related to the principle problems of modern statistical theory and method. Topics surveyed include assessment of probabilities, assessment of utilities, assessment of exchangeability, preposterior analysis, adversary analysis, multiple comparisons, the selection of predictor variables, and full-rank ANOVA. Reference is made to some literature from the field of cognitive psychology to indicate some of the difficulties encountered in probability and utility assessment. Some methods for resolving these difficulties using the Computer-Assisted Data Analysis (CADA) Monitor are described, as is some recent experimental work on utility assessment.1980 Psychometric Society presidential address.I am indebted to Paul Slovic and David Libby for valuable consultation on the issues discussed in this paper and to Nancy Turner and Laura Novick for assistance in preparation.Research reported herein was supported under contract number N00014-77-C-0428 from the Office of Naval Research to The University of Iowa, Melvin R. Novick, principal investigator. Opinions expressed herein reflect those of the author and not those of sponsoring agencies.     

An individual differences additive model: An alterating least squares method with optimal scaling features

An individual differences additive model is discussed which represents individual differences in additivity by differential weighting of additive factors. A procedure for estimating the model parameters for various data measurement characteristics is developed. The procedure is evaluated using both Monte Carlo and real data. The method is found to be very useful in describing certain types of developmental change in cognitive structure, as well as being numerically robust and efficient.The work reported here was partly supported by Grant A6394 to the first author by the Natural Sciences and Engineering Research Council of Canada.     

A note on identification in the oblique and orthogonal factor analysis models

Conditions for removing the indeterminancy due to rotation are given for both the oblique and orthogonal factor analysis models. The conditions indicate why published counterexamples to conditions discussed by Jöreskog are not identifiable.The author would like to thank Gordon Bechtel and the reviewers for their comments and suggestions.     

Power of the likelihood ratio test in covariance structure analysis

A procedure for computing the power of the likelihood ratio test used in the context of covariance structure analysis is derived. The procedure uses statistics associated with the standard output of the computer programs commonly used and assumes that a specific alternative value of the parameter vector is specified. Using the noncentral Chi-square distribution, the power of the test is approximated by the asymptotic one for a sequence of local alternatives. The procedure is illustrated by an example. A Monte Carlo experiment also shows how good the approximation is for a specific case.This research was made possible by a grant from the Dutch Organization for Advancement of Pure Research (ZWO). The authors also like to acknowledge the helpful comments and suggestions from the editor and anonymous reviewers.     

儿童拒绝敏感性与自我知觉的关系:一项交叉滞后研究

采用儿童拒绝敏感性问卷与儿童自我知觉量表对596名中小学儿童进行了为期一年的追踪调查,通过交叉滞后回归分析考察儿童拒绝敏感性与多种自我知觉间的预测关系。结果发现：（1）自我知觉的年级差异显著,初中儿童的自我知觉水平较低;（2）在两次测量中,拒绝敏感性与多种自我知觉均呈显著的负相关;（3）控制性别、年级以及自身稳定性之后,第一年的多种自我知觉均可以负向预测第二年的拒绝敏感性,而第一年的拒绝敏感性仅可以负向预测第二年的体貌及一般自我知觉;（4）年级调节了拒绝敏感性与一般和行为自我知觉间的纵向关系,并在小学与初中儿童中表现出不同的模式。研究证实自我知觉是儿童拒绝敏感性形成的重要原因之一,为儿童社会认知及心理健康的相关研究提供新的实证依据。     

Creating a qualitative typology of electric vehicle driving: EV journey-making mapped in a chronological framework

‘Range anxiety’ is considered a barrier to market acceptance of electric vehicles (EVs), but perceptions of inadequate recharging infrastructure and limited battery range may be part of a more complex set of consumer concerns; experiences and practices of existing EV drivers – with reference to wider transport and energy systems – need to be understood in greater detail. Qualitative material from semi-structured interviews [n = 88] is used to formulate a chronological Typology of Electric Vehicle Driving which synthesises drivers’ decisions, actions and dynamic considerations before, during and after a journey. The typology outlines and tabulates spatio-temporal elements specific to driving an EV; describes adaptations and compromises in household routines and travel habits; draws out how or when drivers engage with external digital information sources – i.e. smartphone apps, social media – during journey-making; plots their intervention in behavioural changes; and could inform development of infrastructure, tools or services, policy or interventions to support EV uptake.     

The association between team‐level social capital and individual‐level work engagement: Differences between subtypes of social capital and the impact of intra‐team agreement

The study explored the association between team‐level social capital and individual‐level work engagement. Questionnaire data were collected from six companies in the dairy industry. Seven hundred seventy‐two participants divided into 65 teams were included. In confirmatory factor analyses, we found a superior model fit to a four dimensional model of social capital: bonding social capital, bridging social capital and two types of linking social capital. The results showed a positive association between all subtypes of social capital at the team level and work engagement at the individual level. However, this association only remained significant for linking social capital in relation the workplace as a whole when we adjusted for psychosocial working conditions. The level of intra‐team agreement in social capital score did not moderate the association between social capital and work engagement. In conclusion, the results provide further support for previous findings suggesting a positive association between social capital and work engagement. They add to the existing knowledge by suggesting that linking social capital in relation to the workplace is the most important explanatory variable for work engagement, thus emphasizing the need to distinguish between subtypes of social capital in research and practice.     

Production planning of Pakistan Tobacco Company (PTC) using quantitative and multiple‐criteria decision analysis—A case in‐point

The main purpose of this paper is to improve the production planning of Pakistan Tobacco Company by selecting the most preferred brand and subsequently generating maximum profit from it. As the company produces a variety of products, the technique of multi criteria decision making is used to select the most preferred brand. To generate the maximum output from the preferred brand, different methods of qualitative managerial analysis are used, which include decision analysis to decide “why and where” the manufacturing should be carried out, transportation model to minimize the logistics cost while meeting the demand, and linear programming technique to maximize the profit generated in 2014–2015. The result obtained from analytical hierarchy process shows that the most preferred brand of the company with respect to price, quality, and comfort is John Player Gold Leaf. The decision analysis explains that this brand should be manufactured in the Jhelum factory of the company as it is more cost‐effective to produce and there is a high availability of resources. Transportation model minimizes the logistics cost of this brand from the 2 factories while meeting the demand at each provinces, central warehouse. Linear programming contributes in generating a profit of 32.738 billion PKR with an amount of 0.35 million PKR, which is more than that of the current profit of the company in the year. These results will allow the top management of the company to take corrective decisions well in time, gain a core competency in cost reduction, and make the supply chain process more efficient.     

Effects of computer‐based training on procedural modifications to standard functional analyses

Few studies have evaluated methods for training decision‐making when functional analysis data are undifferentiated. The current study evaluated computer‐based training to teach 20 graduate students to arrange functional analysis conditions, analyze functional analysis data, and implement procedural modifications. Participants were exposed to training materials using interactive software during a 1‐day session. Following the training, mean scores on the posttest, novel cases probe, and maintenance probe increased for all participants. These results replicate previous findings during a 1‐day session and include a measure of participant acceptability of the training. Recommendations for future research on computer‐based training and functional analysis are discussed.