Why Combine Logics?

Combining logics has become a rapidly expanding entreprise that is inspired mainly by concerns about modularity and the wish to join together tailor made logical tools into more powerful but still manageable ones. A natural question is whether it offers anything new over and above existing standard languages.By analysing a number of applications where combined logics arise, we argue that combined logics are a potentially valuable tool in applied logic, and that endorsements of standard languages often miss the point. Using the history of quantified modal logic as our main example, we also show that the use of combined structures and logics is a recurring theme in the analysis of existing logical systems.     

Linear structural equations with latent variables

An interdependent multivariate linear relations model based on manifest, measured variables as well as unmeasured and unmeasurable latent variables is developed. The latent variables include primary or residual common factors of any order as well as unique factors. The model has a simpler parametric structure than previous models, but it is designed to accommodate a wider range of applications via its structural equations, mean structure, covariance structure, and constraints on parameters. The parameters of the model may be estimated by gradient and quasi-Newton methods, or a Gauss-Newton algorithm that obtains least-squares, generalized least-squares, or maximum likelihood estimates. Large sample standard errors and goodness of fit tests are provided. The approach is illustrated by a test theory model and a longitudinal study of intelligence.This investigation was supported in part by a Research Scientist Development Award (KO2-DA00017) and a research grant (DA01070) from the U. S. Public Health Service.     

More “tricks of the trade”: Reparameterizing LISREL models using negative variances

This paper shows how LISREL may be used to estimate simplex models which impose constraints on the variances of endogenous variables. This technique allows us to estimate both the parameters and the standard errors of the correlated measurement error model proposed by Wiley and Wiley (1974).We would like to thank Jim Wiley for his many helpful comments and suggestions on an earlier draft. We are grateful also to an anonymous reviewer for supplying the EQS program presented in Figure 4.     

Notes for a dialogue between psychoanalysis and neuroscience1

The author postulates that the dialogue between psychoanalysis and neuroscience is based on the assumption that both deal with virtual structures. They are two facets of the same noumenal reality, but with different phenomenal realities, and it is possible to use metapsychology as a lingua franca to develop communication between the two fi elds. In the second part of the paper, the author refl ects on the results of recent neurophysiological research which seem to offer to psychoanalysis possibilities for fi nding an anatomical‐physiological correlate of some well‐known psychic phenomena and mechanisms, such as imitation, introjection, identifi cation, empathy, identity, mother‐child communication, learning, social communication and the analyst‐patient relationship. Particular neurons, called mirror neurons, have been located in the F5 area of baboons' brains. They are also present in man's brain within Broca's area. These neurons activate our motor system during both the performance of actions and the observation of actions performed by others giving rise to an automatic response, a sort of simulation or, rather, imitation, as the process is not intentional, but automatic and unaware, that is, unconscious.     

Identity,Indiscernibility, and Philosophical Claims

The concept of indiscernibility in a structure is analysed with the aim of emphasizing that in asserting that two objects are indiscernible, it is useful to consider these objects as members of (the domain of) a structure. A case for this usefulness is presented by examining the consequences of this view to the philosophical discussion on identity and indiscernibility in quantum theory.     

Recovering a Probabilistic Knowledge Structure by Constraining its Parameter Space

In the Basic Local Independence Model (BLIM) of Doignon and Falmagne (Knowledge Spaces, Springer, Berlin, 1999), the probabilistic relationship between the latent knowledge states and the observable response patterns is established by the introduction of a pair of parameters for each of the problems: a lucky guess probability and a careless error probability. In estimating the parameters of the BLIM with an empirical data set, it is desirable that such probabilities remain reasonably small. A special case of the BLIM is proposed where the parameter space of such probabilities is constrained. A simulation study shows that the constrained BLIM is more effective than the unconstrained one, in recovering a probabilistic knowledge structure.     

The repetition-break plot structure: a cognitive influence on selection in the marketplace of ideas

Using research into learning from sequences of examples, we generate predictions about what cultural products become widely distributed in the social marketplace of ideas. We investigate what we term the Repetition-Break plot structure: the use of repetition among obviously similar items to establish a pattern, and then a final contrasting item that breaks with the pattern to generate surprise. Two corpus studies show that this structure arises in about a third of folktales and story jokes. An experiment shows that jokes with this structure are more interesting than those without the initial repetition. Thus, we document evidence for how a cognitive factor influences the cultural products that are selected in the marketplace of ideas.     

Structural Realism, Scientific Change, and Partial Structures

Scientific change has two important dimensions: conceptual change and structural change. In this paper, I argue that the existence of conceptual change brings serious difficulties for scientific realism, and the existence of structural change makes structural realism look quite implausible. I then sketch an alternative account of scientific change, in terms of partial structures, that accommodates both conceptual and structural changes. The proposal, however, is not realist, and supports a structuralist version of van Fraassen’s constructive empiricism (structural empiricism).     

Latent variable modeling in heterogeneous populations

Common applications of latent variable analysis fail to recognize that data may be obtained from several populations with different sets of parameter values. This article describes the problem and gives an overview of methodology that can address heterogeneity. Artificial examples of mixtures are given, where if the mixture is not recognized, strongly distorted results occur. MIMIC structural modeling is shown to be a useful method for detecting and describing heterogeneity that cannot be handled in regular multiple-group analysis. Other useful methods instead take a random effects approach, describing heterogeneity in terms of random parameter variation across groups. These random effects models connect with emerging methodology for multilevel structural equation modeling of hierarchical data. Examples are drawn from educational achievement testing, psychopathology, and sociology of education. Estimation is carried out by the LISCOMP program.Presidential address delivered at the Psychometric Society meetings in Los Angeles, USA and Leuven, Belgium, July 1989. The research was supported by Grant No. SES-8821668 from the National Science Foundation and by Grant No. OERI-G-86-003 from the Office for Educational Research and Improvement, Department of Education. I thank Leigh Burstein, Mike Hollis, Linda Muthén, and Albert Satorra for helpful discussions and Tammy Tam, Jin-Wen Yang, Suk-Woo Kim, and Lynn Short for computational assistance. Designs were created by Arlette Collier, Rita Ling and Jennifer Edic-Bryant.