138 research outputs found

    A direct approach to individual differences scaling using increasingly complex transformations

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    A family of models for the representation and assessment of individual differences for multivariate data is embodied in a hierarchically organized and sequentially applied procedure called PINDIS. The two principal models used for directly fitting individual configurations to some common or hypothesized space are the dimensional salience and perspective models. By systematically increasing the complexity of transformations one can better determine the validities of the various models and assess the patterns and commonalities of individual differences. PINDIS sheds some new light on the interpretability and general applicability of the dimension weighting approach implemented by the commonly used INDSCAL procedure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45738/1/11336_2005_Article_BF02293810.pd

    The Ernst equation and ergosurfaces

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    We show that analytic solutions \mcE of the Ernst equation with non-empty zero-level-set of \Re \mcE lead to smooth ergosurfaces in space-time. In fact, the space-time metric is smooth near a "Ernst ergosurface" EfE_f if and only if \mcE is smooth near EfE_f and does not have zeros of infinite order there.Comment: 23 pages, 4 figures; misprints correcte

    Physical, cognitive, social and mental health in near-centenarians and centenarians living in New York City: findings from the Fordham Centenarian Study

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    BACKGROUND: Despite their strong increase, the population of the very old, including near-centenarians and centenarians, represent an unstudied and underserved population. Available studies mostly concentrate on predictors of exceptional longevity, but rarely extend their focus to other areas of functioning. Also, little is known about what contributes to experiencing a quality life in very old age. The present population-based study aims at providing a comprehensive picture of key domain of functioning, including physical, cognitive, social and mental function in very old individuals and to determine predictors of mental health indicators. METHODS: A total of 119 individuals aged 95 to 107 living in private dwellings and residential care facilities were recruited based on the New York City Voters Registry. Participants answered questions regarding their health and activities of daily living. Their cognitive functioning was determined using the Mini-Mental State Examination and the Global Deterioration Scale. Social resources were measured with number of children and the Lubben Scale. Mental health was assessed with the Geriatric Depression Scale and the Satisfaction with Life Scale. RESULTS: An unexpectedly large proportion of the sample lived in the community. On average, cognitive functioning was high. Although five diseases were reported on average, participants reported good health. Functional status was reduced. Most participants had at least one person for communication/social support. On average, depression was below cut-off, and most participants reported high life satisfaction. Regression analyses indicated that individual differences in depression were associated with subjective health, IADL and relatives support. For life satisfaction, subjective health, ADL and number of children were most important. Demographic characteristics, number of illnesses or cognitive status were not significant. CONCLUSIONS: Despite reduced levels of physical functioning and social resources, very old participants were in good mental health suggesting high resilience and ability to adapt to age-associated challenges. That a large proportion of them lived in the community further highlights their desire for leading an autonomous life, which may have been facilitated by New York service culture. More research is necessary to provide guidance for the development of well-suited services for this very old population

    A stochastic multidimensional scaling procedure for the empirical determination of convex indifference curves for preference/choice analysis

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    The vast majority of existing multidimensional scaling (MDS) procedures devised for the analysis of paired comparison preference/choice judgments are typically based on either scalar product (i.e., vector) or unfolding (i.e., ideal-point) models. Such methods tend to ignore many of the essential components of microeconomic theory including convex indifference curves, constrained utility maximization, demand functions, et cetera. This paper presents a new stochastic MDS procedure called MICROSCALE that attempts to operationalize many of these traditional microeconomic concepts. First, we briefly review several existing MDS models that operate on paired comparisons data, noting the particular nature of the utility functions implied by each class of models. These utility assumptions are then directly contrasted to those of microeconomic theory. The new maximum likelihood based procedure, MICROSCALE, is presented, as well as the technical details of the estimation procedure. The results of a Monte Carlo analysis investigating the performance of the algorithm as a number of model, data, and error factors are experimentally manipulated are provided. Finally, an illustration in consumer psychology concerning a convenience sample of thirty consumers providing paired comparisons judgments for some fourteen brands of over-the-counter analgesics is discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45748/1/11336_2005_Article_BF02294463.pd

    Carbon monoxide poisoning

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