Single Composite Index Research Articles

Hotspots identification and ranking for road safety improvement: An alternative approach

During the last decade, the concept of composite performance index, brought from economic and business statistics, has become a popular practice in the field of road safety, namely for the identification and classification of worst performing areas or time slots also known as hotspots. The overall quality of a composite index depends upon the complexity of phenomena of interest as well as the relevance of the methodological approach used to aggregate the various indicators into a single composite index. However, current aggregation methods used to estimate the composite road safety performance index suffer from various deficiencies at both the theoretical and operational level; these include the correlation and compensability between indicators, the weighting of the indicators as well as their high “degree of freedom” which enables one to readily manipulate them to produce desired outcomes (Munda and Nardo, 2003, 2005, 2009). The objective of this study is to contribute to the ongoing research effort on the estimation of road safety composite index for hotspots’ identification and ranking. The aggregation method for constructing the composite road safety performance index introduced in this paper, strives to minimize the aforementioned deficiencies of the current approaches. Furthermore, this new method can be viewed as an intelligent decision support system for road safety performance evaluation, in order to prioritize interventions for road safety improvement.

AB0505 Enhanced improvement in physical functioning with secukinumab treatment among RA patients: An application of IRT methodology

BackgroundThe effectiveness of rheumatoid arthritis (RA) treatment in improving physical functioning is most often measured using the HAQ-DI and SF-36v2 physical functioning (PF) scales. Items of the HAQ-DI assess lower...

Using the vulnerable localities index to identify priority areas for targeting fire safety services

The Vulnerable Localities Index (VLI) is a popular analytical method used by police agencies in England and Wales to identify residential neighbourhoods that should be prioritised for attention. The VLI uses data on crime, deprivation and socio-demography to form a single composite index value for small geographic areas, which when mapped can assist in determining where to target neighbourhood policing and crime prevention initiatives. Its use has also helped to prompt other public sector partners such as local municipal government agencies to recognise the collaborative role that they could play with the police in helping to address mutual issues of public safety. Fire safety agencies have also expressed interest in the VLI, but to date this has mainly involved offering a supporting role to the police and local community safety partnerships on crime specific matters of public safety, with a focus on fire safety often on the periphery. In part this is due to limited analysis into whether the priority areas identified by the VLI are also areas of key concern to fire services. This research explores this relationship, identifying that the priority neighbourhoods of interest to the police are also areas where there are significantly higher than expected levels of deliberate fires and malicious false alarm calls to the fire service. These findings suggest that in the spirit of partnership working, potential opportunities exist in achieving mutually beneficial gains in improving public safety through the collaboration of fire, police and other local public service delivery.

A Patient-Centered Methodology That Improves the Accuracy of Prognostic Predictions in Cancer

Individualized approaches to prognosis are crucial to effective management of cancer patients. We developed a methodology to assign individualized 5-year disease-specific death probabilities to 1,222 patients with melanoma and to 1,225 patients with breast cancer. For each cancer, three risk subgroups were identified by stratifying patients according to initial stage, and prediction probabilities were generated based on the factors most closely related to 5-year disease-specific death. Separate subgroup probabilities were merged to form a single composite index, and its predictive efficacy was assessed by several measures, including the area (AUC) under its receiver operating characteristic (ROC) curve. The patient-centered methodology achieved an AUC of 0.867 in the prediction of 5-year disease-specific death, compared with 0.787 using the AJCC staging classification alone. When applied to breast cancer patients, it achieved an AUC of 0.907, compared with 0.802 using the AJCC staging classification alone. A prognostic algorithm produced from a randomly selected training subsample of 800 melanoma patients preserved 92.5% of its prognostic efficacy (as measured by AUC) when the same algorithm was applied to a validation subsample containing the remaining patients. Finally, the tailored prognostic approach enhanced the identification of high-risk candidates for adjuvant therapy in melanoma. These results describe a novel patient-centered prognostic methodology with improved predictive efficacy when compared with AJCC stage alone in two distinct malignancies drawn from two separate populations.

Physician performance assessment using a composite quality index

Assessing physician performance is important for the purposes of measuring and improving quality of service and reducing healthcare delivery costs. In recent years, physician performance scorecards have been used to provide feedback on individual measures; however, one key challenge is how to develop a composite quality index that combines multiple measures for overall physician performance evaluation. A controversy arises over establishing appropriate weights to combine indicators in multiple dimensions, and cannot be easily resolved. In this study, we proposed a generic unsupervised learning approach to develop a single composite index for physician performance assessment by using non-negative principal component analysis. We developed a new algorithm named iterative quadratic programming to solve the numerical issue in the non-negative principal component analysis approach. We conducted real case studies to demonstrate the performance of the proposed method. We provided interpretations from both statistical and clinical perspectives to evaluate the developed composite ranking score in practice. In addition, we implemented the root cause assessment techniques to explain physician performance for improvement purposes.

Analysis of cyclical behaviour of investment expenditures for the Turkish economy

This article aims to analyse the cyclical behaviour of fixed investments in Turkey and then construct a Composite Leading Indicators Index (CLI) to forecast the turning points of investment. The cycles of investment and selected leading indicators are identified following the growth cycle approach. The series are detrended using the Hodrick–Prescott (HP) detrending filter. After identification of the cycles and turning points of the selected leading indicators, they are combined into a single composite index. Then a probit model is estimated to evaluate the forecast performance of the composite index. The results show that the constructed CLI is considered to be helpful in monitoring and predicting investment expenditures.

Spatial Dimensions of Child Social Exclusion Risk in Australia: Widening the Scope

Despite great concern about child well-being, and an increasing recognition of the need to monitor how well children are doing, small area measures of child disadvantage are a very recent development in understanding child well-being both within Australia and internationally. This paper describes the further development of Australia’s only small area index of child social exclusion risk. Drawing on the latest conceptual and methodological developments in child indicator research, the authors have identified additional domains and variables to best measure child social exclusion at a small area level. Incorporating new data, the paper then goes on to discuss the use of principal components analysis and equal weighting to transform the individual indicators into domain scores, and then the domain scores into a single composite index.

Using a Leading Credit Index to Predict Turning Points in the U.S. Business Cycle

Financial indicators such as yield curves and stock prices have been extensively used as leading indicators of economic activity due to their forward looking content. Indeed, the Leading Economic Index (LEI) for the United States, a widely used forecasting tool for business cycle turning points, includes several financial components. However, we argue that the coverage of financial and credit market activity in the LEI can be improved to account for some of the structural changes in the U.S. economy (especially in financial markets) and we present evidence that at least one of the existing components, namely real money supply does not perform as well as it used to as a leading indicator in the past several decades. Over the past three decades, many new financial indicators, such as interest rate swaps, credit default swaps, certain corporate-treasury spreads, the Federal Reserve’s senior loan officer survey, etc. have become available, but, since most of these new indicators have not been available for a long enough period, very little research has been conducted to evaluate their utility as leading indicators. In this paper we evaluate the usefulness of a large number of financial indicators according to their ability to predict recessions (i.e. peaks in the business cycle). First, we establish the criteria which are helpful for assessing whether and when such financial indicators generate signals of recessions. We then choose the best ones and aggregate them into a single composite index of financial indicators which we name the Leading Credit Index (LCI). Our approach differs from others in the literature in that we focus on a small, carefully selected set of indicators as index components and, additionally, in our selection criteria we target business cycle turning points rather than financial stability. We argue that this leading credit index can be helpful to estimate recession probabilities better than individual indicators, including some of the existing components of the LEI, especially real money supply. As opposed to other recent financial indexes created to measure financial instability or volatility, the purpose of ours is to signal recessions in the US economy, and as such it could serve as an appropriate new component for the U.S. LEI.

The congenital diaphragmatic hernia composite prognostic index correlates with survival in left-sided congenital diaphragmatic hernia

Purpose We developed the congenital diaphragmatic hernia congenital prognostic index (CDH-CPI) to incorporate all known prognostic variables into a single composite index to improve prognostic accuracy. The purpose of this study is to examine the ability of the CDH-CPI to predict survival in patients with left-sided congenital diaphragmatic hernia and to determine if the index has a stronger correlation with survival than each of the individual components. Methods A retrospective review of patients with left-sided congenital diaphragmatic hernia between 2004 and 2010 was conducted. Ten prenatal parameters of the CDH-CPI were collected, total score was tabulated, and patients stratified according to total score and survival. Results Sixty-four patients with a prenatal diagnosis of left-sided congenital diaphragmatic hernia were identified. Patients with a CDH-CPI score of 8 or higher had a significantly higher survival than patients with a CDH-CPI score of lower than 8. The CDH-CPI has the strongest correlation with survival compared with the individual parameters measured. The CDH-CPI correlates with extracorporeal membrane oxygenation use, and 75% of patients with a score of 5 or lower were placed on extracorporeal membrane oxygenation. Conclusions The CDH-CPI accurately stratifies survival in left-sided congenital diaphragmatic hernia. The amalgamation of 10 prenatal parameters of the CDH-CPI may be a better prenatal predictor than any single prognostic variable currently used.

Confirmation of a Two-Factor Model for Interpretation of the Comprehensive Trail Making Test with Children

Exploratory factor analyses (EFAs) of the Comprehensive Trail Making Test suggested a possible two-factor solution that might better reflect the differences in Trails 1-3 and Trails 4 and 5 as opposed to a single Composite Index for the total standardization sample. The purpose of this study was to conduct a confirmatory factor analysis (CFA) of the two-factor structure with a subset of the standardization sample ages 18 or younger that had completed all five-trail tasks. The sample included 251 boys and 306 girls, ages 8-18, with a mean age of 12.76 (SD = 3.07). Data were collected across 16 states with representation from all regions of the USA. Standardized scores on each of the trails (1-5) tasks were considered. The results of CFA using M-plus indicated a good fit for the two-factor model, χ(2)(4) = 18.686, p = .0009, root mean-square error of approximation = 0.081, comparative fit index = 0.986 and standardized root-mean-squared residual = 0.021. A one-factor model was not supported. As suggested by the EFA in the manual, Trails 1-3 and Trails 4 and 5, while related, appear to be different in subtle ways that may be most meaningful in conjunction with evaluation of children with neurodevelopmental differences. Implications and possible explanations for this difference are discussed.

Platelet reactivity is a stable and global phenomenon in aspirin-treated cardiovascular patients

In healthy subjects, platelet hyperreactivity is a global phenomenon--as opposed to agonist-specific--and epinephrine-induced platelet aggregation (EPA) is a reliable marker of this phenotype. Few data are available on platelet reactivity and the relationship between EPA and aggregation induced by other agonists in cardiovascular patients. It was the objective of this study to characterise platelet reactivity in stable cardiovascular patients treated with aspirin and to derive a composite index integrating several aggregation pathways, suitable for selecting patients with extreme phenotypes for further proteomics analysis. Platelet reactivity to agonists was assessed in 110 patients twice, two weeks apart. Factorial analysis was used to determine whether the results obtained with the different agonists could be summarised in a single composite index. EPA correlated with the aggregation values obtained with each of the other agonists, with correlation coefficients of 0.44 to 0.55 (p < 0.001). We constructed a composite "platelet reactivity" index that included 60% of the information provided by each agonist. The results obtained at the first patient visit were consistent with those obtained at the second visit (r = 0.78, p<0.01). No clinical or biological parameters correlated with the composite index. The extreme phenotypes of six selected subjects were confirmed 12 months after the second visit. In conclusion, platelet reactivity in aspirin-treated cardiovascular patients is a global phenomenon that can be summarised by a composite index based on the aggregation responses to various agonists and integrating several activation pathways. This index is not dependent on clinical or biological variables, suggesting that genetic factors regulate platelet reactivity in these patients.

The biodiversity quality of butterfly sites: A metadata assessment

1. Recent political agreements mandate that the current rate of biodiversity loss is reduced by 2010 (the 2010 target). In Europe one of the 26 indicators given for this assessment is butterfly biodiversity which therefore requires butterfly biodiversity to be measured. Feest et al. (2010) advocates that this can be done using the concept of “Biodiversity Quality”. 2. “Biodiversity Quality” measurement requires data analysis based on a series of indices examined both independently and jointly, rather than the use of a single measure such as species richness or a single composite index. We show that, where the theoretical base of sampling is sound, data collected with a simple analytical procedure in mind, can generate far more information than envisaged initially. An example of the compilation of “Biodiversity Quality” indicators is given for a site in the Dutch butterfly monitoring scheme (de Vlinderstichting) and two sites are compared for difference. 3. A scheme showing how changes in the different indices might be interpreted to show change in biodiversity quality is given. 4. These butterfly data are important from the perspective of the 2010 targets because: (i) they represent invertebrates, which comprise over half of all terrestrial species; (ii) they are based on relatively long time series; and (iii) they provide a model against which similar programmes can be designed for other taxonomic groups.

Gauging the societal impacts of natural disasters using a capability approach

There is a widely acknowledged need for a single composite index that provides a comprehensive picture of the societal impact of disasters. A composite index combines and logically organizes important information policy-makers need to allocate resources for the recovery from natural disasters; it can also inform hazard mitigation strategies. This paper develops a Disaster Impact Index (DII) to gauge the societal impact of disasters on the basis of the changes in individuals' capabilities. The DII can be interpreted as the disaster impact per capita. Capabilities are dimensions of individual well-being and refer to the genuine opportunities individuals have to achieve valuable states and activities (such as being adequately nourished or being mobile). After discussing the steps required to construct the DII, this article computes and compares the DIIs for two earthquakes of similar magnitude in two societies at different levels of development and of two disasters (earthquake and wind storm) in the same society.

Assessment of temporal trends in ecosystem health using an holistic indicator

The Ecosystem Approach to environmental management, with its explicit acknowledgment of the environmental, social and economic elements within ecological systems, is becoming increasingly adopted by managers and policy makers. However, there are few specific prescriptions as to exactly how these different elements should be integrated, or examples where historical changes have been tracked. Here, we assess the potential benefits and challenges of applying an Ecosystem Approach to management using one particular method, the Holistic Ecosystem Health Indicator (HEHI), which integrates data from the ecological, social and interactive dimensions into a single composite index of ecosystem 'health'. We apply it to one of the best-documented catchments in the UK, the Ythan Estuary in Aberdeenshire, Scotland, based on a 50-year time series of data. The evaluation of ecosystem health over time is lacking in previous applications of HEHI, yet is crucial for the assessment of the utility of this approach to ecosystem management. The application of HEHI yielded different insights to those revealed from the traditional application of biophysical approaches for managing the Ythan. Overall, ecological health declined through the 50-year period, although it increased marginally in the last decade, while social and interactive dimensions followed the opposite trend. HEHI indicated a steady increase in ecosystem health overall except for the last decade, when it declined marginally. Our evaluation of the application of ecosystem health for the Ythan revealed major data gaps. For the approach to be used more widely, issues of data availability and the temporal and geographical mismatch between ecological and social research boundaries need to be overcome.

Structural and functional responses of riparian vegetation to human disturbance: performance and spatial scale-dependence

Successful protection, enhancement and management of surface inland waters require bioassessment and monitoring of ecological quality, as recognized by the Water Framework Directive (WFD; EU/2000/60). In the present paper, we aimed at assessing the response to disturbance of structural and functional components of the riparian ecosystem in order to develop a plant-based index of biotic integrity (Riparian Vegetation index, RVI). Further, the implications of Mediterranean conditions and the spatial scale dependency in the index performance and its component metrics were investigated and discussed. Aquatic and bankside plant species were sampled at more than 400 sites of Portuguese rivers, in Spring-Summer of 2004 and 2005. Over 300 plant attributes were pre-screened to select 32 candidate metrics. Both single stressors and composite stressor indices were used in this study. Two spatial scale-approaches were evaluated: the Local River Type - LRT - which follows the Portuguese river typology, and the Regional River Type - RRT -, which clusters the LRT into North and South types. Compo- sition (e.g. cover and number of alien and endemic species) and functional metrics associated with life cycle and reproduction (e.g. numbers of perennial species), or with trophic status (e.g. proportion of nitrophyllous species) were the most responsive to disturbance across types. Overall, the RVI displayed a reliable response to disturbance; although the local approach has a higher discriminatory effi ciency, the macro scale approach had a more consistent response to multifaceted human disturbances and a more robust performance, essential for environmental-decision making. Results substantiate the hypothesis that plant-based indices of integrity are scale-dependent, an important consideration in the development of typological-adapted methods either for the WFD implementation or for other assessment and monitoring purposes. Future work is required to calibrate the index for inter-annual variability in plant structure and composition, which is especially relevant in Mediterranean-type rivers.

Preliminary Leading Indicators if Employment in New Zealand: Recent Results

The Department o f Labour is currently testing a number of Leading Indicator of Employment (LIoE) series. These indicators are aggregations of different series into a single composite index. The LloE series are designed to give advance warning of turning points in employment. The series have been shown to lead cyclical employment consistently over a long period. Results for recent periods are discussed in more detail as they show deviations from the close historic relationship. This may indicate fundamental shifts in the New Zealand labour market.

Identifying Priority Neighbourhoods Using the Vulnerable Localities Index

The growth of the intelligence-led paradigm in policing and crime reduction partnerships has also called for the need to develop analytical techniques that can aid the development of neighbourhood-level intelligence. A technique that has generated increasing interest in England and Wales to help identify neighbourhoods that require prioritised attention is the Vulnerable Localities Index (VLI). This is a composite measure that is calculated using six variables. The VLI aids the systematic identification of priority neighbourhoods, using a methodology that can be applied in any part of England and Wales (regardless of differences in crime levels), and at any level of geographic scale. It has been pilot tested across eight sites and is gaining particular interest in aiding neighbourhood policing and partnership intelligence requirements. This paper describes the background to the VLI, the criteria that were considered to help identify suitable variables, and the methodology for combining the variables to form a single composite index. This is illustrated with data from Middlesbrough which is then used to demonstrate the VLI's use in practice, illustrating how the Safer Middlesbrough Partnership has used the VLI to support partnership intelligence. Language: en

Real-time commercial availability index of a steam power plant: Graph theory and matrix method

Worldwide, the structure of the power industry is changing to that of a market economy to ensure commercial accountability. Resources, therefore, are allocated for operation and maintenance from commerical considerations rather than technical alone, necessitating the introduction of a commercial approach to analysis of reliabilty, efficiency, and maintenance criticality for power plants. These requirements suggest the need to introduce performance monitoring systems in the form of a single composite index encompassing the consequences of non-performance with respect to all these parameters and which can effectively respond to market demands. Such performance monitoring system is developed in the current paper. Graph theory has been applied to the complex system of a steam power plant to consider its structure explicitly and to derive reliability/availability, efficiency, and maintenance indices. Its representation at system level is modeled by system structure graphs to study reliability/efficiency indices (viz. RTRI and RTEI). The approach has already been applied by the authors for the development of an efficiency index, i.e. RTEI, and a maintenance criticality index to optimize the maintenance cost. In the current paper, it is applied to develop a single composite index, i.e., a real-time commercial availability index (RTAI)com. The various attributes that affect commercial availability are identified as also the interactions among them. With these, a commercial availability attributes' digraph is developed and its corresponding variable permanent commercial availability attribute interaction matrix is written. The permanent function of this matrix is then analysed to study the various aspects of commercial availability as well as to evaluate (RTAI)com. A scheme for implementation of the procedure to develop a single composite index has also been proposed. This will monitor the health of the mechanical equipment of a steam power plant as Supervisory Control and Data Acquisition (SCADA)® monitors its electrical equipment.

Measuring the growth potential of towns in the Western Cape, South Africa

Urban settlements in the Western Cape sustain regional development and are vital to the national spatial economy, but because not all contribute or participate equally they do not grow at the same rate – some flourish while others decline. The Provincial Administration of the Western Cape therefore commissioned a study to evaluate and monitor their functions and performance. This paper assesses the study's methodology and procedures. It describes the variables used and explains how the raw data were transformed into comparative indices and combined into a single composite development potential index. It evaluates the sub-indices and the composite index by mapping the results and uses multivariate statistical techniques to explore the logic and validity of the results. It confirms that the indices created for measuring urban growth potential were well chosen and constructed, laying a sound theoretical and methodological base for future decisions about public investment in rural towns. 1Respectively, Professor (retired); Senior Lecturer; and Research Fellow and Professor (retired), Department of Geography and Environmental Studies, University of Stellenbosch, South Africa.

Fluctuating asymmetry in certain morphological traits in laboratory populations of Drosophila ananassae

Fluctuating asymmetry (FA, subtle random deviations from perfect bilateral symmetry) is often used as a measure of developmental instability (DI), which results from perturbations in developmental pathways caused by genetic or environmental stressors. During the present study, we estimated FA in 5 morphological traits, viz. wing length (WL), wing to thorax ratio (W:T), sternopleural bristle number (SBN), sex-comb tooth number (SCTN), and ovariole number (ON) in 18 laboratory populations of Drosophila ananassae. FA levels of measured traits differed significantly among populations except for SBN (in males and females) and W:T ratio (in females). Positional fluctuating asymmetry (PFA), a sensitive measure of DI, also varied significantly among the populations for SBN in females and SCTN in males. Interestingly, both males and females were similar for nonsexual traits. However, when FA across all traits (sexual and nonsexual) was combined into a single composite index (CFA), significant differences were found for both populations and sexes. Males showed higher CFA values than females, suggesting that males are more prone to developmental perturbations. The magnitude of FA differed significantly among traits, being lowest for nonsexual traits (SBN, WL, W:T ratio) and highest for sexual traits (SCTN and ON). The trait size of sexual traits (SCTN and ON) was positively correlated with their asymmetry. The possible reasons for variation in FA both among traits and among populations, and the usefulness of FA as an indicator of developmental stress and phenotypic quality in D. ananassae are discussed.