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KEY NOTE SPEAKER Sijtsma, Klaas k.sijtsma@uvt.nl Dept. Methodology and Statistics, <strong>Tilburg</strong> School of Social and Behavioral Sciences Title Psychological Measurement Between Physics and Statistics - Klaas Sijtsma Abstract This contribution discusses the physical perspective on psychological measurement represented by additive conjoint measurement and the statistical perspective represented by item response theory, and argues that both fail to adequately address the real measurement problem in psychology: This is the absence of well-developed theories about psychological attributes. I argue that the two perspectives leave psychology out of the equation and by doing that come up with proposals for psychological measurement that are fruitless. Only the rigorous development of attribute theories can lead to meaningful measurement. I provide two examples of the measurement of well-developed attributes and suggest future directions for psychological measurement.
KEY NOTE SPEAKER Snijders, Tom A.B. Tom.Snijders@nuffield.ox.ac.uk Nuffield College <strong>University</strong> of Oxford Title Statistical models for dynamics of social networks: inference and applications Abstract The main issue for statistical modelling of social networks (represented mathematically mainly by directed graphs) is how to express the dependencies between the ties in the network. This is less complicated for longitudinally than for cross-sectionally observed networks, because the time-ordering assists in the representation of these dependencies. Stochastic actor-oriented models are a class of continuous-time Markov chain models for representing network dynamics. These models assume that the actors, represented by the nodes in the network, control their outgoing network ties, subject to inertia and contextual constraints, and with an element of randomness to represent the unpredictability of social behaviour. The transition distribution can depend in potentially complex ways on current network structure and monadic or dyadic covariates. Estimation procedures have been developed for such models using network panel data, i.e., repeated measures of the network collected at two or more discrete time points, according to the method of moments, the maximum likelihood principle, as well as Bayesian methods. The actor-oriented model is presented with an outline of the estimation procedures, and a review is given of some of the applications that have appeared in the literature.
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efore retirement. We identify four
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