Über zwei Formen von Realismus in der Quantentheorie

On Two Types of Realism in Quantum Theory. Current realist approaches to the foundations of quantum theory emphasize the dichotomy between (Copenhagen) positivism and ‘beable’-realism. Recently it was even attempted to turn this picture into two (equally possible) histories in order to legitimate Bohmian Mechanics as a viable alternative. This paper argues that this dichotomy is philosophically inadequate and historically questionable by embedding it into the philosophical discussion on positivism and realism that has taken place since the 1920s. Logical Empiricists back then advocated empirical realism and contrasted it to absolutistic metaphysical realism. From this viewpoint David Bohm's ‘beable’-realism combines elements of Mach's sensualism with a pre-Kantian metaphysics. As Wesley Salmon's position shows, empirical realism can become quite pronounced without relapsing into Bohmian philosophy. Instead it arrives close to the GRWP-interpretation. Hence, when Bernard d'Espagnat binds both together as ‘ontological interpretations’, he blurs the borderline between empirical and metaphysical realism that his Veiled Reality has set out to draw, quite in concordance with Logical Empiricism. This revised version was published online in August 2006 with corrections to the Cover Date.     

AN EMPIRICAL METHOD FOR DETERMINING AN APPROPRIATE INTERVAL LENGTH FOR RECORDING BEHAVIOR

The study sought to examine the effects of varying interval length on the representation of data obtained using modified frequency time sampling. A 7-category scale was used to observe reliably the behavior of eight psychiatric inpatients. Using electronic real time recording equipment, it was possible to computer analyze the obtained data at varying interval lengths, the shortest interval being 1.0 seconds. It was found that increasing the interval length had little effect on the percentage of total duration recorded within each behavioral category, suggesting that this is a relatively stable measure of behavior. Percentage total events for each category was less stable with increasing interval lengths. The number of recorded events within each category tended to decrease, while their average durations tended to increase, as a function of increasing the interval length. The data suggest that the current practice of determining interval length in an arbitrary fashion, or on the basis of convention, should be abandoned. Rather, such a decision should be empirically determined for each particular observation scale and subject group. One method by which this might be achieved is presented.     

Do We “do”?

A normative framework for modeling causal and counterfactual reasoning has been proposed by Spirtes, Glymour, and Scheines (1993; cf. Pearl, 2000). The framework takes as fundamental that reasoning from observation and intervention differ. Intervention includes actual manipulation as well as counterfactual manipulation of a model via thought. To represent intervention, Pearl employed the do operator that simplifies the structure of a causal model by disconnecting an intervened-on variable from its normal causes. Construing the do operator as a psychological function affords predictions about how people reason when asked counterfactual questions about causal relations that we refer to as undoing, a family of effects that derive from the claim that intervened-on variables become independent of their normal causes. Six studies support the prediction for causal (A causes B) arguments but not consistently for parallel conditional (if A then B) ones. Two of the studies show that effects are treated as diagnostic when their values are observed but nondiagnostic when they are intervened on. These results cannot be explained by theories that do not distinguish interventions from other sorts of events.     

A model-based approach to multivariate principal component regression: Selecting principal components and estimating standard errors for unstandardized regression coefficients

Principal component regression (PCR) is a popular technique in data analysis and machine learning. However, the technique has two limitations. First, the principal components (PCs) with the largest variances may not be relevant to the outcome variables. Second, the lack of standard error estimates for the unstandardized regression coefficients makes it hard to interpret the results. To address these two limitations, we propose a model-based approach that includes two mean and covariance structure models defined for multivariate PCR. By estimating the defined models, we can obtain inferential information that will allow us to test the explanatory power of individual PCs and compute the standard error estimates for the unstandardized regression coefficients. A real example is used to illustrate our approach, and simulation studies under normality and nonnormality conditions are presented to validate the standard error estimates for the unstandardized regression coefficients. Finally, future research topics are discussed.     

Marginal maximum likelihood estimation for a psychometric model of discontinuous development

Item response theory models posit latent variables to account for regularities in students' performances on test items. Wilson's “Saltus” model extends the ideas of IRT to development that occurs in stages, where expected changes can be discontinuous, show different patterns for different types of items, or even exhibit reversals in probabilities of success on certain tasks. Examples include Piagetian stages of psychological development and Siegler's rule-based learning. This paper derives marginal maximum likelihood (MML) estimation equations for the structural parameters of the Saltus model and suggests a computing approximation based on the EM algorithm. For individual examinees, empirical Bayes probabilities of learning-stage are given, along with proficiency parameter estimates conditional on stage membership. The MML solution is illustrated with simulated data and an example from the domain of mixed number subtraction. The authors' names appear in alphabetical order. We would like to thank Karen Draney for computer programming, Kikumi Tatsuoka for allowing us to use the mixed-number subtraction data, and Eric Bradlow, Chan Dayton, Kikumi Tatsuoka, and four anonymous referees for helpful suggestions. The first author's work was supported by Contract No. N00014-88-K-0304, R&T 4421552, from the Cognitive Sciences Program, Cognitive and Neural Sciences Division, Office of Naval Research, and by the Program Research Planning Council of Educational Testing Service. The second author's work was supported by a National Academy of Education Spencer Fellowship and by a Junior Faculty Research Grant from the Committee on Research, University of California at Berkeley. A copy of the Saltus computer program can be obtained from the second author.     

General estimators for the reliability of qualitative data

We study a proportional reduction in loss (PRL) measure for the reliability of categorical data and consider the general case in which each ofN judges assigns a subject to one ofK categories. This measure has been shown to be equivalent to a measure proposed by Perreault and Leigh for a special case when there are two equally competent judges, and the correct category has a uniform prior distribution. We consider a general framework where the correct category is assumed to have an arbitrary prior distribution, and where classification probabilities vary by correct category, judge, and category of classification. In this setting, we consider PRL reliability measures based on two estimators of the correct category—the empirical Bayes estimator and an estimator based on the judges' consensus choice. We also discuss four important special cases of the general model and study several types of lower bounds for PRL reliability.Bruce Cooil is Associate Professor of Statistics, and Roland T. Rust is Professor and area head for Marketing, Owen Graduate School of Management, Vanderbilt University. The authors thank three anonymous reviewers and an Associate Editor for their helpful comments and suggestions. This work was supported in part by the Dean's Fund for Faculty Research of the Owen Graduate School of Management, Vanderbilt University.     

Within-session changes in the VI response function: separating food density from elapsed session time.

Previous studies examining the relationship between response rate and reinforcement rate on variable-interval schedules (the variable-interval response function) have confounded elapsed session time with within-session changes in food density. The present experiments attempted to manipulate these factors independently and thus isolate their effects on responding. In Experiment 1, 7 rats pressed a bar for food on a series of four variable-interval schedules (7.5 s, 15 s, 30 s, and 480 s). Elapsed session time was held constant while food density was manipulated via a presession feeding. Changes in food density altered the form of the variable-interval response function, independently of elapsed session time. In Experiment 2, 8 rats responded on the same series of variable-interval schedules as in Experiment 1, but food density was held constant and elapsed session time was manipulated via the use of timeout periods. The results revealed no evidence for an effect of elapsed session time independent of food density. The present results extend a recent analysis of the variable-interval response function by Dougan, Kuh, and Vink (1993) by identifying food density as an important factor determining the form of the function. The present results also help clarify the controversy over the correct empirical form of the variable-interval response function by further defining the variables responsible for differences in the form of that function.     

HOW EMPIRICAL IS WIEMAN'S THEOLOGY?

Abstract. The essay is a response to the papers written by Nancy Frankenberry and Charley Hardwick in the March 1987 issue of Zygon. Questions are raised about whether Wieman's theology is functionalist in the way described by Frankenberry and whether Hardwick's proposal to establish the logical possibility of naturalism as a framework for an existential interpretation of the Christian message is satisfactory. The most basic question raised by both papers is whether Wieman's theology is fully empirical when viewed from the point of view of the radical empiricist.