Controlling for Causally Relevant Third Variables

In 3 experiments, the authors tested the conditions under which 3rd variables are controlled for in making causal judgments. The authors hypothesized that 3rd variables are controlled for when the 3rd variables are themselves perceived as causal. In Experiment 1, the participants predicted test performance after seeing information about wearing a lucky garment, taking a test-preparation course, and staying up late. The course (perceived as more causally relevant) was controlled for more than was the garment (perceived as less causally relevant) in assessing the effectiveness of staying up late. In Experiments 2 and 3, to obviate the many alternative accounts that arise from the realistic cover story of Experiment 1, participants predicted flowers' blooming after the presentation or non-presentation of liquids. When one liquid was trained as causal, it was controlled for more in judging another liquid than when it was trained as neutral. Overall, stimuli perceived as causal were controlled for more when judging other stimuli. The authors concluded that the effect of perceived causal relevance on causal conditionalizing is real and normatively reasonable.     

Model Fit and Item Factor Analysis: Overfactoring,Underfactoring, and a Program to Guide Interpretation

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker–Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.     

A Computationally More Efficient and More Accurate Stepwise Approach for Correcting for Sampling Error and Measurement Error

Over the last decade or two, multilevel structural equation modeling (ML-SEM) has become a prominent modeling approach in the social sciences because it allows researchers to correct for sampling and measurement errors and thus to estimate the effects of Level 2 (L2) constructs without bias. Because the latent variable modeling software Mplus uses maximum likelihood (ML) by default, many researchers in the social sciences have applied ML to obtain estimates of L2 regression coefficients. However, one drawback of ML is that covariance matrices of the predictor variables at L2 tend to be degenerate, and thus, estimates of L2 regression coefficients tend to be rather inaccurate when sample sizes are small. In this article, I show how an approach for stabilizing covariance matrices at L2 can be used to obtain more accurate estimates of L2 regression coefficients. A simulation study is conducted to compare the proposed approach with ML, and I illustrate its application with an example from organizational research.     

Models for the Detection of Deviations from the Expected Processing Strategy in Completing the Items of Cognitive Measures

This paper presents confirmatory factor models with fixed factor loadings that enable the identification of deviations from the expected processing strategy. The instructions usually define the expected processing strategy to a considerable degree. Simplification is a deviation from instructions that is likely to occur in complex cognitive measures. Since simplification impairs the validity of the measure, its identification is important. Models representing simplicity and instruction-based processing strategies were considered in investigating the data of 345 participants obtained by a working memory measure in order to find out whether and how the use of these strategies influences model-data fit. As expected, the consideration of simplicity strategies improved the model-data fit achieved for the instruction-based strategy.     

Los procesos de atribución causal

RESUMEN

El interés por los procesos de atribución, por las explicaciones -razones- que las personas dan para su conducta y la de los demás, es una de las características más sobresalientes de los modelos recientes en la Psicología Social. Heider, hace veinticinco años, ya se había fijado en la gran significación de los procesos de atribución causal en las relaciones interpersonales, pero hasta hace bastantes años después no se recogieron los frutos de aquel interés señalado por Heider. En este trabajo se realiza una revisión de diversos modelos de atribución y se señala, desde una posición crítica, algunas de sus inconsistencias.     

Robot studies on saccade-triggered visual prediction

Three robot studies on visual prediction are presented. In all of them, a visual forward model is used, which predicts the visual consequences of saccade-like camera movements. This forward model works by remapping visual information between the pre- and postsaccadic retinal images; at an abstract modeling level, this process is closely related to neurons whose visual receptive fields shift in anticipation of saccades. In the robot studies, predictive remapping is used (1) in the context of saccade adaptation, to reidentify target objects after saccades are carried out; (2) for a model of grasping, in which both fixated and non-fixated target objects are processed by the same foveal mechanism; and (3) in a computational architecture for mental imagery, which generates “gripper appearances” internally without real sensory inflow. The robotic experiments and their underlying computational models are discussed with regard to predictive remapping in the brain, transsaccadic memory, and attention. The results confirm that visual prediction is a mechanism that has to be considered in the design of artificial cognitive agents and the modeling of information processing in the human visual system.     

Trends in optimization models of sales force management

In the last half-century, significant advances have been made in directing sales force behavior with the use of optimization and decision models. The present paper both presents the current state-of-the art in sales force decision modeling, and also discusses key issues and trends in contemporary modeling of relevance to sales force researchers. The paper begins by exploring critical concepts regarding the estimation of the sales response function, and then discusses critical problems of endogeneity, heterogeneity, and temporal variation that are faced by modelers in this task. Modern approaches to dealing with these issues are presented. We then discuss areas of importance concerning finding model solutions, including closed form versus simulation, and optimization versus heuristic solutions. The paper next moves to areas of practical importance where models can help, including call planning, sales force size, territory allocation, and compensation design. Finally, we discuss trends that will likely impact on sales force modeling in coming years, including the use of big data and data mining, the possible breakdown of rationality, the rise of the Internet and social media, and the potential of agent-based modeling.     

Crystal growth and defect study of BiSbTe3

BiSbTe₃ single crystals have been grown by the Bridgman technique. Microscopic observations of the as-grown crystals reveal typical features, such as striations on the top free surface, which are attributed to the effect of growth conditions. A nitric-acid-based reagent capable of revealing dislocations has been developed and tested. Etch pits are produced at the dislocation sites, but some discrepancies have been observed on matched cleavage surfaces. The structural difference between the matched cleavage surfaces is discussed.     

The World as Representation: Schopenhauer's Arguments for Transcendental Idealism

In this paper, I discuss Spinoza's conception of the cosmological argument for the existence of God (hereafter CA), as it can be reconstructed taking departure from Letter 12. By a CA, I understand, quite broadly, an argument which infers a posteriori the existence of a necessary being, usually identified as God, from the experience that there exists some other being, often oneself, the existence of which is contingent upon the existence of this necessary being. The difference between various versions of the CA stems from differences in the way in which the relation of existential dependence is understood. The aim of this paper is to reconstruct a version of the CA which would be valid on Spinoza's principles. I argue that such a version must be understood in the context of Spinoza's causal rationalism. By such causal rationalism, I mean a doctrine committed to the idea that everything is rational and thus explicable and that causal explanations are somehow fundamental. Moreover, I hold that, in Spinoza's causal rationalism, there is one form of causation through which all other types of causation are ultimately understood. This ‘archetype’ of causation is self-causation.     

Causal Necessity in Aristotle

Like many realists about causation and causal powers, Aristotle uses the language of necessity when discussing causation, and he appears to think that by invoking necessity, he is clarifying the manner in which causes bring about or determine their effects. In so doing, he would appear to run afoul of Humean criticisms of the notion of a necessary connection between cause and effect. The claim that causes necessitate their effects may be understood— or attacked— in several ways, however, and so whether the view or its criticism is tenable depends on how we understand the necessitation claim. In fact, Aristotelian efficient causation may be said to involve two distinct necessary connections: one is a relation between causes considered as potential, while the other relates them considered as active. That is, the claims that (1) what has the power to heat necessarily heats what has the power to be heated, and that (2) a particular flame which is actually under a pot necessarily heats it, both of which appear to be true for Aristotle, involve distinct notions of necessity. The latter kind of necessity is based on the facts, as Aristotle sees them, about change, whereas the former is based in the nature of properties. Though different, both kinds of necessity are instances of what contemporary philosophers would call metaphysical necessity, and together they also amount to a theory of causal determination.