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Discrete Multivariate Analysis: Theory and Practice
, 1975
"... the collaboration of Richard J. Light and Frederick Mosteller. ..."
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the collaboration of Richard J. Light and Frederick Mosteller.
A framework for understanding the allocation of attention in locationprecued discrimination
 Quarterly Journal of Experimental Psychology
, 1994
"... The effects of attention on visual perception are assessed in the locationprecuing paradigm. First, we present a review of some current metaphors for attention and relevant data. Then, a framework is suggested that provides an interpretation of the temporal sequence of external and assumed internal ..."
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Cited by 9 (0 self)
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The effects of attention on visual perception are assessed in the locationprecuing paradigm. First, we present a review of some current metaphors for attention and relevant data. Then, a framework is suggested that provides an interpretation of the temporal sequence of external and assumed internal processes within a locationcuing trial. Cases when a precue correctly indicates the target location (valid trials) are compared to cases when the precue directs attention to the wrong location (invalid trials) with the cue location either at fixation or peripheral to the target location. Several specific hypotheses are suggested; these concern decrements in performance on invalid trials and effects of the location of a precue. For the most part, these hypotheses are supported by data in the literature and in some new studies. A gradientfilter metaphor for attention, which includes a synthesis of ideas from the gradient model and the attention gate model, is more consistent with the data than is a spotlight metaphor.
D: Linear versus nonlinear methods of sire evaluation for categorical traits: a simulation study. Gen Sel Evol
, 1985
"... Linear (BLUP) and nonlinear (GFCAT) methods of sire evaluation for categorical data were compared using Monte Carlo techniques. Binary and ordered tetrachotomous responses were generated from an underlying normal distribution via fixed thresholds, so as to model incidences in the population as a who ..."
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Cited by 6 (0 self)
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Linear (BLUP) and nonlinear (GFCAT) methods of sire evaluation for categorical data were compared using Monte Carlo techniques. Binary and ordered tetrachotomous responses were generated from an underlying normal distribution via fixed thresholds, so as to model incidences in the population as a whole. Sires were sampled from a normal distribution and family structure consisted of halfsib groups of equal or unequal size; simulations were done at several levels of heritability (h2). When a oneway model was tenable or when responses were tetrachotomous, the differences between the 2 methods were negligible. However, when responses were binary, the layout was highly unbalanced and a mixed model was appropriate to describe the underlying variate, GFCAT elicited significantly larger responses to truncation selection than BLUP at h2.20 or.50 and when the incidence in the = population was below 25 p. 100. The largest observed difference in selection efficiency between the 2 methods was 12 p. 100.
Three Centuries of Categorical Data Analysis: Loglinear Models and Maximum Likelihood Estimation
"... The common view of the history of contingency tables is that it begins in 1900 with the work of Pearson and Yule, but it extends back at least into the 19th century. Moreover it remains an active area of research today. In this paper we give an overview of this history focussing on the development o ..."
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The common view of the history of contingency tables is that it begins in 1900 with the work of Pearson and Yule, but it extends back at least into the 19th century. Moreover it remains an active area of research today. In this paper we give an overview of this history focussing on the development of loglinear models and their estimation via the method of maximum likelihood. S. N. Roy played a crucial role in this development with two papers coauthored with his students S. K. Mitra and Marvin Kastenbaum, at roughly the midpoint temporally in this development. Then we describe a problem that eluded Roy and his students, that of the implications of sampling zeros for the existence of maximum likelihood estimates for loglinear models. Understanding the problem of nonexistence is crucial to the analysis of large sparse contingency tables. We introduce some relevant results from the application of algebraic geometry to the study of this statistical problem. 1
Two causal theories of counterfactual conditionals
 Cognitive Science
, 2010
"... Bayes nets are formal representations of causal systems that many psychologists have claimed as plausible mental representations. One purported advantage of Bayes nets is that they may provide a theory of counterfactual conditionals, such as If Calvin had been at the party, Miriam would have left ea ..."
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Cited by 4 (1 self)
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Bayes nets are formal representations of causal systems that many psychologists have claimed as plausible mental representations. One purported advantage of Bayes nets is that they may provide a theory of counterfactual conditionals, such as If Calvin had been at the party, Miriam would have left early. This article compares two proposed Bayesnet theories as models of people’s understanding of counterfactuals. Experiments 13 show that neither theory makes correct predictions about backtracking counterfactuals (in which the event of the ifclause occurs after the event of the thenclause), and Experiment 4 shows the same is true of forward counterfactuals. An amended version of one of the approaches, however, can provide a more accurate account of these data. Counterfactuals, Forward and Backward / 3 1.
Some applications of categorical data analysis to epidemiological studies. Environ. Health Perspect. 32: 000
, 1979
"... Several examples of categorized data from epidemiological studies are analyzed to illustrate that more informative analysis than tests of independence can be performed by fitting models. All of the analyses fit into a unified conceptual framework that can be performed by weighted least squares. The ..."
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Several examples of categorized data from epidemiological studies are analyzed to illustrate that more informative analysis than tests of independence can be performed by fitting models. All of the analyses fit into a unified conceptual framework that can be performed by weighted least squares. The methods presented show how to calculate point estimate of parameters, asymptotic variances, and asymptotically valid x2 tests. The examples presented are analysis of relative risks estimated from several 2 x 2 tables, analysis of selected features of life tables, construction of synthetic life tables from crosssectional studies, and analysis of doseresponse curves.
Algebraic Descriptions of Nominal Multivariate Discrete Data
 J. Multivariate Anal
, 1995
"... Traditionally, multivariate discrete data are analyzed by means of loglinear models. In this paper we show how an algebraic approach leads naturally to alternative models, parametrized in terms of the moments of the distribution. Moreover we derive a complete characterization of all meaningful tran ..."
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Traditionally, multivariate discrete data are analyzed by means of loglinear models. In this paper we show how an algebraic approach leads naturally to alternative models, parametrized in terms of the moments of the distribution. Moreover we derive a complete characterization of all meaningful transformations of the components and show how transformations affect the moments of a distribution. It turns out that our models provide the necessary formal description of longitudinal data; moreover in the classical case, they can be considered as an analysis tool, complementary to loglinear models. 1 Introduction We start with a given multivariate discrete nominal variable X. Questions of interest about X can be roughly divided into two groups. One group is related to conditional characteristics such as conditional independencies or questions concerning the sign and/or magnitude of logodds ratios. The other group focuses on marginal characteristics such as marginal independencies or multiv...
Local Estimators in Multivariate Generalized Linear Models With VaryingCoefficients
, 1997
"... Introduction In varyingcoefficient models as considered by Hastie & Tibshirani (1993) coefficients are allowed to change smoothly across the value of other variables, the socalled effect modifiers. That means one has two types of regressors, the usual covariate x and the effect modifier u. For th ..."
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Introduction In varyingcoefficient models as considered by Hastie & Tibshirani (1993) coefficients are allowed to change smoothly across the value of other variables, the socalled effect modifiers. That means one has two types of regressors, the usual covariate x and the effect modifier u. For the wide class of multivariate 2 generalized linear models the varyingcoefficient type has the form E(yjx; u) = h(Z(x)fi(u)) (1) where h : IR q ! IR q is the response function, Z(x) is a design matrix composed from covariates x and fi(u) is the parameter vector varying across values of u. If fi(u) is non varying but a fixed c