64 research outputs found

    Modelling Kinship with LISP - A Two-Sex Model of Kin-Counts

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    The crucial problem related to aging is how to provide support for the increasing proportion of the elderly. The measure and way of this support depends on the kinship pattern for a particular population. The paper develops the approach to modeling the kinship. The results of modeling show that the approach can be successfully implemented to the analysis of the family dynamics

    Double Jeopardy in Inferring Cognitive Processes

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    Inferences we make about underlying cognitive processes can be jeopardized in two ways due to problematic forms of aggregation. First, averaging across individuals is typically considered a very useful tool for removing random variability. The threat is that averaging across subjects leads to averaging across different cognitive strategies, thus harming our inferences. The second threat comes from the construction of inadequate research designs possessing a low diagnostic accuracy of cognitive processes. For that reason we introduced the systems factorial technology (SFT), which has primarily been designed to make inferences about underlying processing order (serial, parallel, coactive), stopping rule (terminating, exhaustive), and process dependency. SFT proposes that the minimal research design complexity to learn about n number of cognitive processes should be equal to 2n. In addition, SFT proposes that (a) each cognitive process should be controlled by a separate experimental factor, and (b) The saliency levels of all factors should be combined in a full factorial design. In the current study, the author cross combined the levels of jeopardies in a 2 × 2 analysis, leading to four different analysis conditions. The results indicate a decline in the diagnostic accuracy of inferences made about cognitive processes due to the presence of each jeopardy in isolation and when combined. The results warrant the development of more individual subject analyses and the utilization of full-factorial (SFT) experimental designs

    A cognitive latent variable model for the simultaneous analysis of behavioral and personality data

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    I describe a cognitive latent variable model, a combination of a cognitive model and a latent variable model that can be used to aggregate information regarding cognitive parameters across participants and tasks. The model is ideally suited for uncovering relationships between latent task abilities as they are expressed in experimental paradigms, but can also be used as data fusion tools to connect latent abilities with external covariates from entirely different data sources. An example application deals with the structure of cognitive abilities underlying an executive functioning task and its relation to personality traits. © 2014 Elsevier Inc

    Analisis del hogar en base a datos censales, Bolivia 1976

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