1,720,969 research outputs found

    Parametric tests of perfect judgment ranking based on ordered ranked set samples

    No full text
    We develop parametric and location-scale free tests of perfect judgment ranking based on ordered ranked set samples. The tests are based on the differences between the elements of the ordered ranked set samples and those of the original ranked set samples. We compare our proposed tests with the best existing tests of perfect judgment ranking in the literature by using Monte Carlo simulation. Our simulation results show that the proposed tests behave favorably in comparison with their leading competitors, especially under the fraction of neighbor rankings model. In comparison to the nonparametric competitors, the proposed tests have the advantage of not needing randomization to attain a specific size

    Enhanced one-sided confidence regions for a multivariate location parameter

    No full text
    AbstractIf a one-sided test for a multivariate location parameter is inverted, the resulting confidence region may have an unpleasant shape. In particular, if the null and alternative hypothesis are both composite and complementary, the confidence region usually does not resemble the alternative parameter region in shape, but rather a reflected version of the null parameter region.We illustrate this effect and show one possibility of obtaining confidence regions for the location parameter that are smaller and have a more suitable shape for the type of problems investigated. This method is based on the closed testing principle applied to a family of nested hypotheses

    Going Beyond Counting First Authors in Author Co-citation Analysis

    Get PDF
    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Some nonparametric tests of perfect judgment ranking for judgment post stratification

    Get PDF
    We develop some nonparametric tests of perfect judgment ranking for judgment post stratification sampling scheme. We show that the best proposed test beats the best existing nonparametric test of perfect judgment ranking in ranked set sampling applied to the judgment post stratification case by conditioning on the observed stratum sizes

    Intervals for the assessment of measurement agreement: Similarities, differences, and consequences of incorrect interpretations

    No full text
    Several intervals have been proposed to quantify the agreement of two methods intended to measure the same quantity in the situation where only one measurement per method and subject is available. The limits of agreement are probably the most well-known among these intervals, which are all based on the differences between the two measurement methods. The different meanings of the intervals are not always properly recognized in applications. However, at least for small-to-moderate sample sizes, the differences will be substantial. This is illustrated both using the width of the intervals and on probabilistic scales related to the definitions of the intervals. In particular, for small-to-moderate sample sizes, it is shown that limits of agreement and prediction intervals should not be used to make statements about the distribution of the differences between the two measurement methods or about a plausible range for all future differences. Care should therefore be taken to ensure the correct choice of the interval for the intended interpretation
    corecore