978 resultados para Stated preference methods


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Recent research suggests that the retrospective review of the International Classification of Disease (ICD-9-CM) codes assigned to a patient episode will identify a similar number of healthcare-acquired surgical-site infections as compared with prospective surveillance by infection control practitioners (ICP). We tested this finding by replicating the methods for 380 surgical procedures. The sensitivity and specificity of the ICP undertaking prospective surveillance was 80% and 100%, and the sensitivity and specificity of the review of ICD-10-AM codes was 60% and 98.9%. Based on these results we do not support retrospective review of ICD-10-AM codes in preference prospective surveillance for SSI. (C) 2004 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

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The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios. Copyright (C) 2005 John Wiley & Sons, Ltd.

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Functionally-fitted methods are generalizations of collocation techniques to integrate an equation exactly if its solution is a linear combination of a chosen set of basis functions. When these basis functions are chosen as the power functions, we recover classical algebraic collocation methods. This paper shows that functionally-fitted methods can be derived with less restrictive conditions than previously stated in the literature, and that other related results can be derived in a much more elegant way. The novelty in our approach is to fully retain the collocation framework without reverting back into derivations based on cumbersome Taylor series expansions.

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Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.

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Purpose - The purpose of this paper is to examine consumer emotions and the social science and observation measures that can be utilised to capture the emotional experiences of consumers. The paper is not setting out to solve the theoretical debate surrounding emotion research, rather to provide an assessment of methodological options available to researchers to aid their investigation into both the structure and content of the consumer emotional experience, acknowledging both the conscious and subconscious elements of that experience. Design/methodology/approach - A review of a wide range of prior research from the fields of marketing, consumer behaviour, psychology and neuroscience are examined to identify the different observation methods available to marketing researchers in the study of consumer emotion. This review also considers the self report measures available to researchers and identifies the main theoretical debates concerning emotion to provide a comprehensive overview of the issues surrounding the capture of emotional responses in a marketing context and to highlight the benefits that observation methods offer this area of research. Findings - This paper evaluates three observation methods and four widely used self report measures of emotion used in a marketing context. Whilst it is recognised that marketers have shown preference for the use of self report measures in prior research, mainly due to ease of implementation, it is posited that the benefits of observation methodology and the wealth of data that can be obtained using such methods can compliment prior research. In addition, the use of observation methods cannot only enhance our understanding of the consumer emotion experience but also enable us to collaborate with researchers from other fields in order to make progress in understanding emotion. Originality/value - This paper brings perspectives and methods together to provide an up to date consideration of emotion research for marketers. In order to generate valuable research in this area there is an identified need for discussion and implementation of the observation techniques available to marketing researchers working in this field. An evaluation of a variety of methods is undertaken as a point to start discussion or consideration of different observation techniques and how they can be utilised.

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Multiple regression analysis is a complex statistical method with many potential uses. It has also become one of the most abused of all statistical procedures since anyone with a data base and suitable software can carry it out. An investigator should always have a clear hypothesis in mind before carrying out such a procedure and knowledge of the limitations of each aspect of the analysis. In addition, multiple regression is probably best used in an exploratory context, identifying variables that might profitably be examined by more detailed studies. Where there are many variables potentially influencing Y, they are likely to be intercorrelated and to account for relatively small amounts of the variance. Any analysis in which R squared is less than 50% should be suspect as probably not indicating the presence of significant variables. A further problem relates to sample size. It is often stated that the number of subjects or patients must be at least 5-10 times the number of variables included in the study.5 This advice should be taken only as a rough guide but it does indicate that the variables included should be selected with great care as inclusion of an obviously unimportant variable may have a significant impact on the sample size required.

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Selecting the best alternative in a group decision making is a subject of many recent studies. The most popular method proposed for ranking the alternatives is based on the distance of each alternative to the ideal alternative. The ideal alternative may never exist; hence the ranking results are biased to the ideal point. The main aim in this study is to calculate a fuzzy ideal point that is more realistic to the crisp ideal point. On the other hand, recently Data Envelopment Analysis (DEA) is used to find the optimum weights for ranking the alternatives. This paper proposes a four stage approach based on DEA in the Fuzzy environment to aggregate preference rankings. An application of preferential voting system shows how the new model can be applied to rank a set of alternatives. Other two examples indicate the priority of the proposed method compared to the some other suggested methods.

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A Közgazdasági Szemle márciusi számában Telcs és szerzőtársai [2013] a felvételizők preferenciái alapján új megközelítést javasolt a felsőoktatási intézmények rangsorolására. Az alábbi írás új szempontokat biztosít ezen alapötlet gyakorlati megvalósításához. Megmutatja, hogy az alkalmazott modell ekvivalens az alternatívák egy aggregált páros összehasonlítási mátrix révén végzett rangsorolásával, ami rávilágít a szerzők kiinduló hipotéziseinek vitatható pontjaira. A szerző röviden áttekinti a hasonló feladatok megoldására javasolt módszereket, különös tekintettel azok axiomatikus megalapozására, majd megvizsgálja a Telcs és szerzőtársai [2013] által alkalmazott eljárásokat. Végül említést tesz egy hasonló megközelítéssel élő cikkről, és megfogalmaz néhány, a vizsgálat továbbfejlesztésére vonatkozó javaslatot. _____ In the March issue of Közgazdasági Szemle, Telcs et al. suggested a new approach to university ranking through preference ordering of applicants. The paper proposes new aspects to the implementation of this idea. It is shown that the model of these is equivalent to the ranking of alternatives based on paired comparisons, which reveals the debatable points in their hypotheses. The author reviews briefly the methods proposed in the literature, focusing on their axiomatic properties, and thoroughly examines the procedures of Telcs et al. [2013]. The paper presents an article which applied a similar approach and suggests some improvements to it.

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Since the damage of the onion thrips (Thrips tabaci Lindemann) first occurred on white cabbage in Hungary several observations have been carried out, both in Hungary and abroad, to assess varietal resistance. The use of a new evaluation method for field screening is described and the result of the monitoring of 64 varieties is reported. The most susceptible varieties were ‘Bejo 1860’, ‘SG 3164’, ‘Quisto’, ‘Green Gem’ and ‘Ramada’. On the other hand, ‘Golden Cross’, ‘Balashi’, ‘Riana’, ‘Autumn Queen’, ‘Leopard’, Ama-Daneza’ and ‘Galaxy’ suffered the least damage under natural infestation. Methods for testing the patterns of resistance are also described and evaluated. In case of plants at the few leaf growth stage significant negative correlation was found between egg mortality and the egg laying preference of adults. The results of the other antibiotic and antixenotic tests were greatly affected by differences in the physiological age and condition of the varieties.

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How children rate vegetables may be influenced by the preparation method. The primary objective of this study was for first grade students to be involved in a cooking demonstration and to taste and rate vegetables raw and cooked. First grade children of two classes (N= 52: 18 boys and 34 girls (approximately half Hispanic) that had assented and had signed parental consent participated in the study. The degree of liking a particular vegetable was recorded by the students using a hedonic scale of five commonly eaten vegetables tasted first raw (pre-demonstration) and then cooked (post-demonstration). A food habit questionnaire was filled out by parents to evaluate their mealtime practices and beliefs about their child’s eating habits. Paired sample t-tests revealed significant differences in preferences for vegetables in their raw and cooked states. Several mealtime characteristics were significantly associated with children’s vegetable preferences. Parents who reported being satisfied with how often the family eats evening meals together were more likely to report that their child eats adequate vegetables for their health (p=0.026). Parents who stated that they were satisfied with their child’s eating habits were more likely to report that their child was trying new foods (p<.001). Cooking demonstrations by nutrition professionals may be an important strategy that can be used by parents and teachers to promote vegetable intake. It is important that nutrition professionals provide guidance to encourage consumption of vegetables for parents so that they can model the behavior of healthy food consumption to their children.

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Objectives: The current study aims to evaluate dosage form preferences in children and young adults together with identifying the key pragmatic dosage form characteristics that would enable appropriate formulation of orally disintegrating tablets (ODTs). Methods: International, multisite, cross-sectional questionnaire of children and young adults aged from 6 to 18 years. Eligibility was based on age, ability to communicate and previous experience in taking medications. The study was carried out at three locations: the UK, Saudi Arabia and Jordan. The questionnaire instrument was designed for participant self-completion under supervision of the study team.Results 104 questionnaires were completed by the study cohort (n=120, response rate 87%). Results: showed that ODTs were the most preferred oral dosage forms (58%) followed by liquids (20%), tablets (12%) and capsules (11%). The preferred colours were pink or white while the preferred size was small (<8 mm) with a round shape. With regard to flavour, strawberry was the most preferred (30.8%), while orange was the least preferred (5.8%). The results also showed that the most important physical characteristics of ODTs were disintegration time followed by taste, size and flavour, respectively. Conclusions: The results of our study support the WHO's claim for a shift of paradigm from liquid towards ODTs dosage forms for drug administration to young children older than 6 years. Data from this study will also equip formulators to prioritise development of key physical/performance attributes within the delivery system.

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Consumers have relationships with other people, and they have relationships with brands similar to the ones they have with other people. Yet, very little is known about how brand and interpersonal relationships relate to one another. Even less is known about how they jointly affect consumer well-being. The goal of this research, therefore, is to examine how brand and interpersonal relationships influence and are influenced by consumer well-being. Essay 1 uses both empirical methods and surveys from individuals and couples to investigate how consumer preferences in romantic couples, namely brand compatibility, influences life satisfaction. Using traditional statistical techniques and multilevel modeling, I find that the effect of brand compatibility, or the extent to which individuals have similar brand preferences, on life satisfaction depends upon power in the relationship. For high power partners, brand compatibility has no effect on life satisfaction. On the other hand, for low power partners, low brand compatibility is associated with decreased life satisfaction. I find that conflict mediates the link between brand compatibility and power on life satisfaction. In Essay 2 I again use empirical methods and surveys to investigate how resources, which can be considered a form of consumer well-being, influence brand and interpersonal relations. Although social connections have long been considered a fundamental human motivation and deemed necessary for well-being (Baumeister and Leary 1995), recent research has demonstrated that having greater resources is associated with weaker social connections. In the current research I posit that individuals with greater resources still have a need to connect and are using other sources for connection, namely brands. Across several studies I test and find support for my theory that resource level shifts the preference of social connection from people to brands. Specifically, I find that individuals with greater resources have stronger brand relationships, as measured by self-brand connection, brand satisfaction, purchase intentions and willingness to pay with both existing brand relationships and with new brands. This suggests that individuals with greater resources place more emphasis on these relationships. Furthermore, I find that resource level influences the stated importance of brand and interpersonal relationships, and that having or perceiving greater resources is associated with an increased preference to engage with brands over people. This research demonstrates that there are times when people prefer and seek out connections with brands over other people, and highlights the ways in which our brand and interpersonal relationships influence one another.

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INTRODUCTION: The differential associations of beer, wine, and spirit consumption on cardiovascular risk found in observational studies may be confounded by diet. We described and compared dietary intake and diet quality according to alcoholic beverage preference in European elderly.

METHODS: From the Consortium on Health and Ageing: Network of Cohorts in Europe and the United States (CHANCES), seven European cohorts were included, i.e. four sub-cohorts from EPIC-Elderly, the SENECA Study, the Zutphen Elderly Study, and the Rotterdam Study. Harmonized data of 29,423 elderly participants from 14 European countries were analyzed. Baseline data on consumption of beer, wine, and spirits, and dietary intake were collected with questionnaires. Diet quality was assessed using the Healthy Diet Indicator (HDI). Intakes and scores across categories of alcoholic beverage preference (beer, wine, spirit, no preference, non-consumers) were adjusted for age, sex, socio-economic status, self-reported prevalent diseases, and lifestyle factors. Cohort-specific mean intakes and scores were calculated as well as weighted means combining all cohorts.

RESULTS: In 5 of 7 cohorts, persons with a wine preference formed the largest group. After multivariate adjustment, persons with a wine preference tended to have a higher HDI score and intake of healthy foods in most cohorts, but differences were small. The weighted estimates of all cohorts combined revealed that non-consumers had the highest fruit and vegetable intake, followed by wine consumers. Non-consumers and persons with no specific preference had a higher HDI score, spirit consumers the lowest. However, overall diet quality as measured by HDI did not differ greatly across alcoholic beverage preference categories.

DISCUSSION: This study using harmonized data from ~30,000 elderly from 14 European countries showed that, after multivariate adjustment, dietary habits and diet quality did not differ greatly according to alcoholic beverage preference.

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Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.