12,224 research outputs found

    Investigating invariant item ordering in the Mental Health Inventory : an illustration of the use of different methods

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    Invariant item ordering is a property of scales whereby the items are scored in the same order across a wide range of the latent trait and across a wide range of respondents. In the package ‘mokken’ in the statistical software R, the ability to analyse Mokken scales for invariant item ordering has recently been available and techniques for inspecting visually the item response curves of item pairs, have also been included. While methods to assess invariant item ordering are available, there have been indications that items representing extremes of distress in mental well-being scales, such as suicidal ideation, may lead to claiming invariant item ordering where it does not exist. We used the Mental Health Inventory to see if invariant item ordering was indicated in any Mokken scales derived and to see if this was being influenced by extreme items. A Mokken scale was derived indicating invariant item ordering. Visual inspection of the item pairs indicated that the most difficult item (suicidal ideation) was located far from the remaining cluster of items. Removing this item lowered invariant item ordering to an unacceptable level

    Cardiac Depression Scale: Mokken scaling in heart failure patients

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    Background: There is a high prevalence of depression in patients with heart failure (HF) that is associated with worsening prognosis. The value of using a reliable and valid instrument to measure depression in this population is therefore essential. We validated the Cardiac Depression Scale (CDS) in heart failure patients using a model of ordinal unidimensional measurement known as Mokken scaling. Findings: We administered in face-to-face interviews the CDS to 603 patients with HF. Data were analysed using Mokken scale analysis. Items of the CDS formed a statistically significant unidimensional Mokken scale of low strength (H<0.40) and high reliability (Rho>0.8). Conclusions: The CDS has a hierarchy of items which can be interpreted in terms of the increasingly serious effects of depression occurring as a result of HF. Identifying an appropriate instrument to measure depression in patients with HF allows for early identification and better medical management. Keywords: Cardiac Depression Scale, Heart failure, Depression, Mokken scalin

    An SMP Soft Classification Algorithm for Remote Sensing

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    This work introduces a symmetric multiprocessing (SMP) version of the continuous iterative guided spectral class rejection (CIGSCR) algorithm, a semiautomated classification algorithm for remote sensing (multispectral) images. The algorithm uses soft data clusters to produce a soft classification containing inherently more information than a comparable hard classification at an increased computational cost. Previous work suggests that similar algorithms achieve good parallel scalability, motivating the parallel algorithm development work here. Experimental results of applying parallel CIGSCR to an image with approximately 10^8 pixels and six bands demonstrate superlinear speedup. A soft two class classification is generated in just over four minutes using 32 processors

    Violations of local stochastic independence exaggerate scalability in Mokken scaling analysis of the Chinese Mandarin SF-36

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    Background: Previous work using Mokken scaling analysis with the SF-36 has found subscales appearing to show excellent Mokken scaling properties. However, the values of scalability of the subscales are very large, raising the possibility that these are artificially high and this may result from violations of local stochastic independence between items. Objectives: To analyse selected items from the Chinese Mandarin form of the SF-36 scale using Mokken scaling and to investigate if violations of local stochastic independence exaggerate scalability. Methods: Exploratory Mokken scaling analysis was run using the online public domain software R by entering 19 items from the Chinese Mandarin form of the SF-36 items into the analysis. The items in the resulting scales, judged by the size of Loevinger’s coefficient, were analysed for violations of monotony, 95% confidence intervals and invariant item ordering, including inspection of item pair plots. Results: Two Mokken scales were obtained, one including items from the Physical Functioning subscale, and one including items from the Mental Health subscale of the Chinese Mandarin form of the SF-36. The Physical Functioning scale was very strong according to Loevinger’s coefficient with high invariant item ordering; the Mental Health scale was moderately strong with weak invariant item ordering. Conclusion: The strength of the Physical Functioning Mokken scale derived from the Chinese Mandarin form of the SF-36 is probably the result of an item chain and item overlap which violate local stochastic independence. This is due to the nature of the items in the Physical Functioning subscale, all of which relate to physical ability and some of which can only be achieved if previous items in the subscale have been achieved

    Rac-1 and IQGAP are potential regulators of E-cadherin-catenin interactions during murine preimplantation development.

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    Adherens junction formation is fundamental for compaction and trophectoderm differentiation during mammalian preimplantation development. We recently isolated an IQGAP-2 cDNA from a differential display-polymerase chain reaction screen of bovine preimplantation developmental stages. IQGAP-1 and -2 proteins mediate E-cadherin-based cell-to-cell adhesion through interactions with beta-catenin and the Rho GTPases, rac1 and cdc42. Our study demonstrates IQGAP-1,-2, rac-1 and cdc42 mRNAs are present throughout murine preimplantation development. IQGAP-1 and rac-1 protein distribution changes from predominantly plasma membrane associated to predominantly cytoplasmic as the embryo progresses through cleavage divisions and compaction to the blastocyst stage

    Parallel Deterministic and Stochastic Global Minimization of Functions with Very Many Minima

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    The optimization of three problems with high dimensionality and many local minima are investigated under five different optimization algorithms: DIRECT, simulated annealing, Spall’s SPSA algorithm, the KNITRO package, and QNSTOP, a new algorithm developed at Indiana University

    Nursing schools: dumbing down or reaching up?

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    Universities and their nursing faculties are changing dramatically. Rather than serving as bastions of knowledge generation, professional innovation, curation and dissemination of knowledge, many have become corporatised monoliths intent on a perverse form of utilitarianism on steroids. Their sole function it seems is to produce commoditised ‘outputs’ that can contribute to the ‘knowledge economy’
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