903 resultados para hierarchical (multilevel) analysis


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This paper introduces an extended hierarchical task analysis (HTA) methodology devised to evaluate and compare user interfaces on volumetric infusion pumps. The pumps were studied along the dimensions of overall usability and propensity for generating human error. With HTA as our framework, we analyzed six pumps on a variety of common tasks using Norman’s Action theory. The introduced method of evaluation divides the problem space between the external world of the device interface and the user’s internal cognitive world, allowing for predictions of potential user errors at the human-device level. In this paper, one detailed analysis is provided as an example, comparing two different pumps on two separate tasks. The results demonstrate the inherent variation, often the cause of usage errors, found with infusion pumps being used in hospitals today. The reported methodology is a useful tool for evaluating human performance and predicting potential user errors with infusion pumps and other simple medical devices.

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This study contributes to research regarding the value of children (VOC) by comparing adolescents' VOC and their intentions to have children across 12 cultures and by exploring the relations between these constructs at the individual and cultural levels using multilevel modeling. A total of 3,348 adolescents from 12 cultures participated in this study. On average, adolescents reported that they intended to have about two children and also reported emotional VOC as being highly important. Adolescents from cultures with a low as compared to a high level of economic development reported a higher importance of the utilitarian-normative VOC. Results of the multilevel analyses showed that the reported emotional VOC was positively related to the number of children adolescents intended to have at the individual level, whereas the utilitarian-normative VOC was not related to adolescents' intention to have children. At the cultural level, the VOC dimensions were only partly related to adolescents' intention to have children. The results are discussed with regard to adolescents' future family orientation and in relation to the VOC approach.

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Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^

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BACKGROUND In contrast to objective structured clinical examinations (OSCEs), mini-clinical evaluation exercises (mini-CEXs) take place at the clinical workplace. As both mini-CEXs and OSCEs assess clinical skills, but within different contexts, this study aims at analyzing to which degree students' mini-CEX scores can be predicted by their recent OSCE scores and/or context characteristics. METHODS Medical students participated in an end of Year 3 OSCE and in 11 mini-CEXs during 5 different clerkships of Year 4. The students' mean scores of 9 clinical skills OSCE stations and mean 'overall' and 'domain' mini-CEX scores, averaged over all mini-CEXs of each student were computed. Linear regression analyses including random effects were used to predict mini-CEX scores by OSCE performance and characteristics of clinics, trainers, students and assessments. RESULTS A total of 512 trainers in 45 clinics provided 1783 mini-CEX ratings for 165 students; OSCE results were available for 144 students (87 %). Most influential for the prediction of 'overall' mini-CEX scores was the trainers' clinical position with a regression coefficient of 0.55 (95 %-CI: 0.26-0.84; p < .001) for residents compared to heads of department. Highly complex tasks and assessments taking place in large clinics significantly enhanced 'overall' mini-CEX scores, too. In contrast, high OSCE performance did not significantly increase 'overall' mini-CEX scores. CONCLUSION In our study, Mini-CEX scores depended rather on context characteristics than on students' clinical skills as demonstrated in an OSCE. Ways are discussed which focus on either to enhance the scores' validity or to use narrative comments only.

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This study applies the multilevel analysis technique to longitudinal data of a large clinical trial. The technique accounts for the correlation at different levels when modeling repeated blood pressure measurements taken throughout the trial. This modeling allows for closer inspection of the remaining correlation and non-homogeneity of variance in the data. Three methods of modeling the correlation were compared. ^

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Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^

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Objective: To determine the effect of inequalities in income within a state on self rated health status while controlling for individual characteristics such as socioeconomic status.

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Individuals from the same population share a number of contextual circumstances that may condition a common level of blood pressure over and above individual characteristics. Understanding this population effect is relevant for both etiologic research and prevention strategies. Using multilevel regression analyses, the authors quantified the extent to which individual differences in systolic blood pressure (SBP) could be attributed to the population level. They also investigated possible cross-level interactions between the population in which a person lived and pharmacological (antihypertensive medication) and nonpharmacological (body mass index) effects on individual SBP. They analyzed data on 23,796 men and 24,986 women aged 35-64 years from 39 worldwide Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) study populations participating in the final survey of this World Health Organization project (1989-1997). SBP was positively associated with low educational achievement, high body mass index, and use of antihypertensive medication and, for women, was negatively associated with smoking. About 7-8% of all SBP differences between subjects were attributed to the population level. However, this population effect was particularly strong (i.e., 20%) in antihypertensive medication users and overweight women. This empirical evidence of a population effect on individual SBP emphasizes the importance of developing population-wide strategies to reduce individual risk of hypertension.