157 resultados para preference-based measures


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Background: To derive preference-based measures from various condition-specific descriptive health-related quality of life (HRQOL) measures. A general 2-stage method is evolved: 1) an item from each domain of the HRQOL measure is selected to form a health state classification system (HSCS); 2) a sample of health states is valued and an algorithm derived for estimating the utility of all possible health states. The aim of this analysis was to determine whether confirmatory or exploratory factor analysis (CFA, EFA) should be used to derive a cancer-specific utility measure from the EORTC QLQ-C30. Methods: Data were collected with the QLQ-C30v3 from 356 patients receiving palliative radiotherapy for recurrent or metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter based on a conceptual model (the established domain structure of the QLQ-C30: physical, role, emotional, social and cognitive functioning, plus several symptoms) and clinical considerations (views of both patients and clinicians about issues relevant to HRQOL in cancer). The dimensions determined by each method were then subjected to item response theory, including Rasch analysis. Results: CFA results generally supported the proposed conceptual model, with residual correlations requiring only minor adjustments (namely, introduction of two cross-loadings) to improve model fit (increment χ2(2) = 77.78, p < .001). Although EFA revealed a structure similar to the CFA, some items had loadings that were difficult to interpret. Further assessment of dimensionality with Rasch analysis aligned the EFA dimensions more closely with the CFA dimensions. Three items exhibited floor effects (>75% observation at lowest score), 6 exhibited misfit to the Rasch model (fit residual > 2.5), none exhibited disordered item response thresholds, 4 exhibited DIF by gender or cancer site. Upon inspection of the remaining items, three were considered relatively less clinically important than the remaining nine. Conclusions: CFA appears more appropriate than EFA, given the well-established structure of the QLQ-C30 and its clinical relevance. Further, the confirmatory approach produced more interpretable results than the exploratory approach. Other aspects of the general method remain largely the same. The revised method will be applied to a large number of data sets as part of the international and interdisciplinary project to develop a multi-attribute utility instrument for cancer (MAUCa).

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Background Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. Aim To determine whether confirmatory factor analysis (CFA) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of Cancer’s core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. Methods QLQ-C30 (Version 3) data were collected from 356 patients receiving palliative radiotherapy for recurrent/metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter informed by the established QLQ-C30 structure and views of both patients and clinicians on which are the most relevant items. Dimensions determined by EFA or CFA were then subjected to Rasch analysis. Results CFA results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker–Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by CFA. Conclusion CFA was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new cancer-specific MAUI. Our findings suggest that CFA should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.

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In [8] the authors developed a logical system based on the definition of a new non-classical connective ⊗ capturing the notion of reparative obligation. The system proved to be appropriate for handling well-known contrary-to-duty paradoxes but no model-theoretic semantics was presented. In this paper we fill the gap and define a suitable possible-world semantics for the system for which we can prove soundness and completeness. The semantics is a preference-based non-normal one extending and generalizing semantics for classical modal logics.

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Previously, expected satiety (ES) has been measured using software and two-dimensional pictures presented on a computer screen. In this context, ES is an excellent predictor of self-selected portions, when quantified using similar images and similar software. In the present study we sought to establish the veracity of ES as a predictor of behaviours associated with real foods. Participants (N = 30) used computer software to assess their ES and ideal portion of three familiar foods. A real bowl of one food (pasta and sauce) was then presented and participants self-selected an ideal portion size. They then consumed the portion ad libitum. Additional measures of appetite, expected and actual liking, novelty, and reward, were also taken. Importantly, our screen-based measures of expected satiety and ideal portion size were both significantly related to intake (p < .05). By contrast, measures of liking were relatively poor predictors (p > .05). In addition, consistent with previous studies, the majority (90%) of participants engaged in plate cleaning. Of these, 29.6% consumed more when prompted by the experimenter. Together, these findings further validate the use of screen-based measures to explore determinants of portion-size selection and energy intake in humans.

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BACKGROUND:Previous epidemiological investigations of associations between dietary glycemic intake and insulin resistance have used average daily measures of glycemic index (GI) and glycemic load (GL). We explored multiple and novel measures of dietary glycemic intake to determine which was most predictive of an association with insulin resistance.METHODS:Usual dietary intakes were assessed by diet history interview in women aged 42-81 years participating in the Longitudinal Assessment of Ageing in Women. Daily measures of dietary glycemic intake (n = 329) were carbohydrate, GI, GL, and GL per megacalorie (GL/Mcal), while meal based measures (n = 200) were breakfast, lunch and dinner GL; and a new measure, GL peak score, to represent meal peaks. Insulin resistant status was defined as a homeostasis model assessment (HOMA) value of >3.99; HOMA as a continuous variable was also investigated.RESULTS:GL, GL/Mcal, carbohydrate (all P < 0.01), GL peak score (P = 0.04) and lunch GL (P = 0.04) were positively and independently associated with insulin resistant status. Daily measures were more predictive than meal-based measures, with minimal difference between GL/Mcal, GL and carbohydrate. No significant associations were observed with HOMA as a continuous variable.CONCLUSION:A dietary pattern with high peaks of GL above the individual's average intake was a significant independent predictor of insulin resistance in this population, however the contribution was less than daily GL and carbohydrate variables. Accounting for energy intake slightly increased the predictive ability of GL, which is potentially important when examining disease risk in more diverse populations with wider variations in energy requirements.

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Previous research employing indirect measures of arch structure, such as those derived from footprints, have indicated that obesity results in a “flatter” foot type. In the absence of radiographic measures, however, definitive conclusions regarding the osseous alignment of the foot cannot be made. We determined the effect of body mass index (BMI) on radiographic and footprint‐based measures of arch structure. The research was a cross‐sectional study in which radiographic and footprint‐based measures of foot structure were made in 30 subjects (10 males, 20 female) in addition to standard anthropometric measures of height, weight, and BMI. Multiple (univariate) regression analysis demonstrated that both BMI ( β  = 0.39, t 26  = 2.12, p  = 0.04) and radiographic arch alignment ( β  = 0.51, t 26  = 3.32, p  < 0.01) were significant predictors of footprint‐based measures of arch height after controlling for all variables in the model ( R 2  = 0.59, F 3,26  = 12.3, p  < 0.01). In contrast, radiographic arch alignment was not significantly associated with BMI ( β  = −0.03, t 26  = −0.13, p  = 0.89) when Arch Index and age were held constant ( R 2  = 0.52, F 3,26  = 9.3, p  < 0.01). Adult obesity does not influence osseous alignment of the medial longitudinal arch, but selectively distorts footprint‐based measures of arch structure. Footprint‐based measures of arch structure should be interpreted with caution when comparing groups of varying body composition.

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he purpose of this study was to evaluate the comparative cost of treating alcohol dependence with either cognitive behavioral therapy (CBT) alone or CBT combined with naltrexone (CBT+naltrexone). Two hundred ninety-eight outpatients dependent on alcohol who were consecutively treated for alcohol dependence participated in this study. One hundred seven (36%) patients received adjunctive pharmacotherapy (CBT+naltrexone). The Drug Abuse Treatment Cost Analysis Program was used to estimate treatment costs. Adjunctive pharmacotherapy (CBT+naltrexone) introduced an additional treatment cost and was 54% more expensive than CBT alone. When treatment abstinence rates (36.1% CBT; 62.6% CBT+naltrexone) were applied to cost effectiveness ratios, CBT+naltrexone demonstrated an advantage over CBT alone. There were no differences between groups on a preference-based health measure (SF-6D). In this treatment center, to achieve 100 abstainers over a 12-week program, 280 patients require CBT compared with 160 CBT+naltrexone. The dominant choice was CBT+naltrexone based on modest economic advantages and significant efficiencies in the numbers needed to treat.

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Boards of directors are thought to provide access to a wealth of knowledge and resources for the companies they serve, and are considered important to corporate governance. Under the Resource Based View (RBV) of the firm (Wernerfelt, 1984) boards are viewed as a strategic resource available to firms. As a consequence there has been a significant research effort aimed at establishing a link between board attributes and company performance. In this thesis I explore and extend the study of interlocking directorships (Mizruchi, 1996; Scott 1991a) by examining the links between directors’ opportunity networks and firm performance. Specifically, I use resource dependence theory (Pfeffer & Salancik, 1978) and social capital theory (Burt, 1980b; Coleman, 1988) as the basis for a new measure of a board’s opportunity network. I contend that both directors’ formal company ties and their social ties determine a director’s opportunity network through which they are able to access and mobilise resources for their firms. This approach is based on recent studies that suggest the measurement of interlocks at the director level, rather than at the firm level, may be a more reliable indicator of this phenomenon. This research uses publicly available data drawn from Australia’s top-105 listed companies and their directors in 1999. I employ Social Network Analysis (SNA) (Scott, 1991b) using the UCINET software to analyse the individual director’s formal and social networks. SNA is used to measure a the number of ties a director has to other directors in the top-105 company director network at both one and two degrees of separation, that is, direct ties and indirect (or ‘friend of a friend’) ties. These individual measures of director connectedness are aggregated to produce a board-level network metric for comparison with measures of a firm’s performance using multiple regression analysis. Performance is measured with accounting-based and market-based measures. Findings indicate that better-connected boards are associated with higher market-based company performance (measured by Tobin’s q). However, weaker and mostly unreliable associations were found for accounting-based performance measure ROA. Furthermore, formal (or corporate) network ties are a stronger predictor of market performance than total network ties (comprising social and corporate ties). Similarly, strong ties (connectedness at degree-1) are better predictors of performance than weak ties (connectedness at degree-2). My research makes four contributions to the literature on director interlocks. First, it extends a new way of measuring a board’s opportunity network based on the director rather than the company as the unit of interlock. Second, it establishes evidence of a relationship between market-based measures of firm performance and the connectedness of that firm’s board. Third, it establishes that director’s formal corporate ties matter more to market-based firm performance than their social ties. Fourth, it establishes that director’s strong direct ties are more important to market-based performance than weak ties. The thesis concludes with implications for research and practice, including a more speculative interpretation of these results. In particular, I raise the possibility of reverse causality – that is networked directors seek to join high-performing companies. Thus, the relationship may be a result of symbolic action by companies seeking to increase the legitimacy of their firms rather than a reflection of the social capital available to the companies. This is an important consideration worthy of future investigation.

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Earlier research developed theoretically-based aggregate metrics for technology strategy and used them to analyze California bridge construction firms (Hampson, 1993). Determinants of firm performance, including trend in contract awards, market share and contract awards per employee, were used as indicators for competitive performance. The results of this research were a series of refined theoretically-based measures for technology strategy and a demonstrated positive relationship between technology strategy and competitive performance within the bridge construction sector. This research showed that three technology strategy dimensions—competitive positioning, depth of technology strategy, and organizational fit— show very strong correlation with the competitive performance indicators of absolute growth in contract awards, and contract awards per employee. Both researchers and industry professionals need improved understanding of how technology affects results, and how to better target investments to improve competitive performance in particular industry sectors. This paper builds on the previous research findings by evaluating the strategic fit of firms' approach to technology with industry segment characteristics. It begins with a brief overview of the background regarding technology strategy. The major sections of the paper describe niches and firms in an example infrastructure construction market, analyze appropriate technology strategies, and describe managerial actions to implement these strategies and support the business objectives of the firm.

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This paper develops a composite participation index (PI) to identify patterns of transport disadvantage in space and time. It is operationalised using 157 weekly activity-travel diaries data collected from three case study areas in rural Northern Ireland. A review of activity space and travel behaviour research found that six dimensional indicators of activity spaces were typically used including the number of unique locations visited, distance travelled, area of activity spaces, frequency of activity participation, types of activity participated in, and duration of participation in order to identify transport disadvantage. A combined measure using six individual indices were developed based on the six dimensional indicators of activity spaces, by taking into account the relativity of the measures for weekdays, weekends, and for a week. Factor analyses were conducted to derive weights of these indices to form the PI measure. Multivariate analysis using general linear models of the different indicators/indices identified new patterns of transport disadvantage. The research found that: indicator based measures and index based measures are complement each other; interactions between different factors generated new patterns of transport disadvantage; and that these patterns vary in space and time. The analysis also indicates that the transport needs of different disadvantaged groups are varied.

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This paper identifies transport disadvantage using a 7 day activity-travel diary data from two rural case study areas. A composite participation index (PI) measure was developed for this study based on six indices measuring elements of travel and activity participation. Using the index the paper then goes on to compare these results, with the results obtained from other more traditional indicators used to identify transport disadvantage. These indicators are related to the size of activity space such as unique network distance travelled, number of unique locations visited, activity space area, activity duration, and fullness (shape) of activity spaces. The weaknesses of these indicator based measures are that: firstly, they do not take into account the relativity of the measure between different areas i.e. travel distance in terms of the wider context of available activities within an area; and secondly, these indicators are multi-dimensional and each represents a different qualitative aspect of travel and activity participation. As a result, six individual indices were developed to overcome these problems. These include: participation count index, participation length index, participation area index, participation duration index, participation type index, and participation frequency index. These are then aggregated to assess the relative performance in terms of these different indices and identify the nature of transport disadvantage. GIS was used to visualise individual travel patterns and to derive scores for both the indicator based measures and the index based measures. Factor analysis was conducted to derive weights of the individual indices to form the composite index measure. From this analysis, two intermediate indices were also derived using the underlying factors of the data related to these indices. Using the scores of all these measures, multiple regression analyses were conducted to identify patterns of transport disadvantage.

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This paper presents an input-orientated data envelopment analysis (DEA) framework which allows the measurement and decomposition of economic, environmental and ecological efficiency levels in agricultural production across different countries. Economic, environmental and ecological optimisations search for optimal input combinations that minimise total costs, total amount of nutrients, and total amount of cumulative exergy contained in inputs respectively. The application of the framework to an agricultural dataset of 30 OECD countries revealed that (i) there was significant scope to make their agricultural production systemsmore environmentally and ecologically sustainable; (ii) the improvement in the environmental and ecological sustainability could be achieved by being more technically efficient and, even more significantly, by changing the input combinations; (iii) the rankings of sustainability varied significantly across OECD countries within frontier-based environmental and ecological efficiency measures and between frontier-based measures and indicators.

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This paper examines the relationship between financial performance and ethical screening intensity of a special class of ethical funds that is rooted in Islamic values – Islamic equity funds (IEFs). These faith-based ethical funds screen investments on compliance with Islamic values where conventional interest expense (riba), gambling (maysir), excessive uncertainty (gharar), and non-ethical (non-halal) products are prohibited. We test whether these extra screens affect the financial performance of IEFs relative to non-Islamic funds. Based on a large survivorship-free international sample of 387 Islamic funds, our results show that IEFs on average underperform conventional funds by 40 basis points per month, or 4.8% per year (supporting the underperformance hypothesis). While Islamic funds do not generally perform better during crisis periods, they outperformed conventional funds during the recent sub-prime crisis (supporting the outperformance hypothesis). Using holdings-based measures for ethical screening intensity, results show IEFs that apply more intensive screening perform worse, suggesting that there is a cost to being ethical.

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Objectives The purpose of the study was to establish regression equations that could be used to predict muscle thickness and pennation angle at different intensities from electromyography (EMG) based measures of muscle activation during isometric contractions. Design Cross-sectional study. Methods Simultaneous ultrasonography and EMG were used to measure pennation angle, muscle thickness and muscle activity of the rectus femoris and vastus lateralis muscles, respectively, during graded isometric knee extension contractions performed on a Cybex dynamometer. Data form fifteen male soccer players were collected in increments of approximately 25% intensity of the maximum voluntary contraction (MVC) ranging from rest to MVC. Results There was a significant correlation (P < 0.05) between ultrasound predictors and EMG measures for the muscle thickness of rectus femoris with an R2 value of 0.68. There was no significant correlation (P > 0.05) between ultrasound pennation angle for the vastus lateralis predictors for EMG muscle activity with an R2 value of 0.40. Conclusions The regression equations can be used to characterise muscle thickness more accurately and to determine how it changes with contraction intensity, this provides improved estimates of muscle force when using musculoskeletal models.