Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data betwee…
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Toxic compounds, such as pesticides, are routinely tested against a range of aquatic, avian and mammalian species as part of the registration process. The need for reducing dependence on animal testing has led to an increasing interest in alternative methods such as in silico mo…
Data quality is an important aspect of an organisation’s strategies for supporting decision makers in reaching the best decisions possible and consequently attaining the organisation’s objectives. In the case of public organisations, decisions ultimately concern the public and h…
`Active Ageing' has been promoted by the World Health Organisation (WHO) as a strategy for promoting the health and well-being of older people. Keeping active and involved in a range of activities not restricted to those associated with labour market participation may, it has be…
The literature identifies perceptions of data quality as a key factor influencing a wide range of attitudes and behaviors related to data in organizational settings (e.g. decision confidence). In particular, there is an overwhelming consensus that effective customer relationship…
Poor quality data such as data with errors or missing values cause negative consequences in many application domains. An important aspect of data quality is completeness. One problem in data completeness is the problem of missing individuals in data sets. Within a data set, the …