167,260 research outputs found

    Chi, Lotta L. -- 1986-92 -- Correspondence, Individual -- letter, 1987-03-17

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    Letter from Chi, Lotta Li to Sabin, Albert B. dated 1987-03-17.Sabin Collection Fair Use Policy</a

    Chi, Lotta L. -- 1986-92 -- Correspondence, Individual -- letter, 1991-03-07

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    Letter from Chi, Lotta Li to Sabin, Albert B. dated 1991-03-07.Sabin Collection Fair Use Policy</a

    Chi, Lotta L. -- 1986-92 -- Correspondence, Individual -- letter, 1990-08-23

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    Letter from Chi, Lotta Li to Sabin, Albert B. dated 1990-08-23.Sabin Collection Fair Use Policy</a

    Maximally selected chi-square statistics and umbrella orderings

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    Binary outcomes that depend on an ordinal predictor in a non-monotonic way are common in medical data analysis. Such patterns can be addressed in terms of cutpoints: for example, one looks for two cutpoints that define an interval in the range of the ordinal predictor for which the probability of a positive outcome is particularly high (or low). A chi-square test may then be performed to compare the proportions of positive outcomes in and outside this interval. However, if the two cutpoints are chosen to maximize the chi-square statistic, referring the obtained chi-square statistic to the standard chi-square distribution is an inappropriate approach. It is then necessary to correct the p-value for multiple comparisons by considering the distribution of the maximally selected chi-square statistic instead of the nominal chi-square distribution. Here, we derive the exact distribution of the chi-square statistic obtained by the optimal two cutpoints. We suggest a combinatorial computation method and illustrate our approach by a simulation study and an application to varicella data

    Monotonicity of Chi-square Test Statistics

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    This paper establishes monotonicity of the chi-square test statistic. As the more efficient parameter estimator is plugged into the test statistic, the degrees of freedom of the resulting chi-square test statistic monotonically increase.

    Ar-CHI-tecture: Architecture and Interaction

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    The rise of ubiquitous computing leads to a natural convergence between the areas of architectural design (the design of buildings, spaces and experience of being in and moving through them) and HCI. We suggest that Architecture and CHI have much to learn from each other in terms of research and practice. This workshop will bring together these communities to explore the benefits of architecture envisioned as integral to an expanded CHI community. The workshop organizers aim to create a framework for future collaboration and identify new directions for research in this multidisciplinary field. This promises significant impacts on both interaction research and its real-world applications
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