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Introduction: Quality of life is included in the economic evaluation of health services by measuring the preference for health states, i.e. health state utilities. However, most intervention studies include a disease-specific, not a utility, instrument. Consequently, there has been increasing use of statistical mapping algorithms which permit utilities to be estimated from a disease-specific instrument. The present paper provides such algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and six multi-attribute utility (MAU) instruments, the Euroqol (EQ-5D), the Short Form 6D (SF-6D), the Health Utilities Index (HUI) 3, the Quality of Wellbeing (QWB), the 15D (15 Dimension) and the Assessment of Quality of Life (AQoL-8D). Methods: Heart disease patients and members of the healthy public were recruited from six countries. Non-parametric rank tests were used to compare subgroup utilities and MacNew scores. Mapping algorithms were estimated using three separate statistical techniques. Results: Mapping algorithms achieved a high degree of precision. Based on the mean absolute error and the intra class correlation the preferred mapping is MacNew into SF-6D or 15D. Using the R squared statistic the preferred mapping is MacNew into AQoL-8D. Implications for research: The algorithms reported in this paper enable MacNew data to be mapped into utilities predicted from any of six instruments. This permits studies which have included the MacNew to be used in cost utility analyses which, in turn, allows the comparison of services with interventions across the health system. [ABSTRACT FROM AUTHOR]

ABSTRACT We present a detailed analysis of four of the most widely used radio source-finding packages in radio astronomy, and a program being developed for the Australian Square Kilometer Array Pathfinder telescope. The four packages: sextractor, sfind, imsad and selavy are shown to produce source catalogues with high completeness and reliability. In this paper we analyse the small fraction (∼1 per cent) of cases in which these packages do not perform well. This small fraction of sources will be of concern for the next generation of radio surveys which will produce many thousands of sources on a daily basis, in particular for blind radio transients surveys. From our analysis we identify the ways in which the underlying source-finding algorithms fail. We demonstrate a new source-finding algorithm aegean, based on the application of a Laplacian kernel, which can avoid these problems and can produce complete and reliable source catalogues for the next generation of radio surveys. [ABSTRACT FROM AUTHOR]