The potential for bias in reporting of industry-sponsored clinical trials

Concerns about potentially misleading reporting of pharmaceutical industry research have surfaced many times. The potential for duality (and thereby conflict) of interest is only too clear when you consider the sums of money required for the discovery, development and commercialization of new medicines. As the ability of major, mid-size and small pharmaceutical companies to innovate has waned, as evidenced by the seemingly relentless decline in the numbers of new medicines approved by Food and Drug Administration and European Medicines Agency year-on-year, not only has the cost per new approved medicine risen: so too has the public and media concern about the extent to which the pharmaceutical industry is open and honest about the efficacy, safety and quality of the drugs we manufacture and sell. In 2005 an Editorial in Journal of the American Medical Association made clear that, so great was their concern about misleading reporting of industry-sponsored studies, henceforth no article would be published that was not also guaranteed by independent statistical analysis. We examine the precursors to this Editorial, as well as its immediate and lasting effects for statisticians, for the manner in which statistical analysis is carried out, and for the industry more generally.

Combined bias and outlier identification in dynamic data reconciliation

Measured process data normally contain inaccuracies because the measurements are obtained using imperfect instruments. As well as random errors one can expect systematic bias caused by miscalibrated instruments or outliers caused by process peaks such as sudden power fluctuations. Data reconciliation is the adjustment of a set of process data based on a model of the process so that the derived estimates conform to natural laws. In this paper, techniques for the detection and identification of both systematic bias and outliers in dynamic process data are presented. A novel technique for the detection and identification of systematic bias is formulated and presented. The problem of detection, identification and elimination of outliers is also treated using a modified version of a previously available clustering technique. These techniques are also combined to provide a global dynamic data reconciliation (DDR) strategy. The algorithms presented are tested in isolation and in combination using dynamic simulations of two continuous stirred tank reactors (CSTR).

Water reuse for irrigation in Jordan: plant beneficial nutrients, farmers’ awareness and management strategies

The reuse of treated wastewater (reclaimed water) is particularly well suited for irrigated agriculture as it often contains significant quantities of plant essential nutrients. This work has shown that reclaimed water in Jordan can have adequate concentrations of potassium, phosphate, sulphate and magnesium to meet all or part of the crop’s requirements. To fully benefit from these inputs farmers must have an awareness of the water quality and reduce the application of chemical fertilisers accordingly. Interviews with farmers have shown that 75 per cent of farmers indirectly using reclaimed water are aware of the nutrients. Farmers’ decision making as to the application of chemical fertilisers appears to be influenced by a range of factors which include the type of crops being cultivated, the provision of training on nutrient management and the availability of information on the nutrient content of the reclaimed water.

Examination of long-wave radiative bias in general circulation models over North Africa during May–July

Satellite data are used to quantify and examine the bias in the outgoing long-wave (LW) radiation over North Africa during May–July simulated by a range of climate models and the Met Office global numerical weather prediction (NWP) model. Simulations from an ensemble-mean of multiple climate models overestimate outgoing clear-sky long-wave radiation (LWc) by more than 20 W m−2 relative to observations from Clouds and the Earth's Radiant Energy System (CERES) for May–July 2000 over parts of the west Sahara, and by 9 W m−2 for the North Africa region (20°W–30°E, 10–40°N). Experiments with the atmosphere-only version of the High-resolution Hadley Centre Global Environment Model (HiGEM), suggest that including mineral dust radiative effects removes this bias. Furthermore, only by reducing surface temperature and emissivity by unrealistic amounts is it possible to explain the magnitude of the bias. Comparing simulations from the Met Office NWP model with satellite observations from Geostationary Earth Radiation Budget (GERB) instruments suggests that the model overestimates the LW by 20–40 W m−2 during North African summer. The bias declines over the period 2003–2008, although this is likely to relate to improvements in the model and inhomogeneity in the satellite time series. The bias in LWc coincides with high aerosol dust loading estimated from the Ozone Monitoring Instrument (OMI), including during the GERBILS field campaign (18–28 June 2007) where model overestimates in LWc greater than 20 W m−2 and OMI-estimated aerosol optical depth (AOD) greater than 0.8 are concurrent around 20°N, 0–20°W. A model-minus-GERB LW bias of around 30 W m−2 coincides with high AOD during the period 18–21 June 2007, although differences in cloud cover also impact the model–GERB differences. Copyright © Royal Meteorological Society and Crown Copyright, 2010

Interpretation bias and anxiety in childhood: stability, specificity and longitudinal associations

Background: Biases in the interpretation of ambiguous material are central to cognitive models of anxiety; however, understanding of the association between interpretation and anxiety in childhood is limited. To address this, a prospective investigation of the stability and specificity of anxious cognitions and anxiety and the relationship between these factors was conducted. Method: Sixty-five children (10–11 years) from a community sample completed measures of self-reported anxiety, depression, and conduct problems, and responded to ambiguous stories at three time points over one-year. Results: Individual differences in biases in interpretation of ambiguity (specifically “anticipated distress” and “threat interpretation”) were stable over time. Furthermore, anticipated distress and threat interpretation were specifically associated with anxiety symptoms. Distress anticipation predicted change in anxiety symptoms over time. In contrast, anxiety scores predicted change in threat interpretation over time. Conclusions: The results suggest that different cognitive constructs may show different longitudinal links with anxiety. These preliminary findings extend research and theory on anxious cognitions and their link with anxiety in children, and suggest that these cognitive processes may be valuable targets for assessment and intervention.

Changing standards revisited: children’s awareness and knowledge of features of written standard English at ages 10-11

This paper reports the findings of a small-scale research project which investigated the levels of awareness and knowledge of written standard English of 10 and 11 year old children in two English primary schools. The project involved repeating in 2010 a written questionnaire previously used with children in the same schools in three separate surveys in 1999, 2002 and 2005. Data from the latest survey are compared to those from the previous three. The analysis seeks to identify any changes over time in children’s ability to recognise non-standard forms and supply standard English alternatives, as well as their ability to use technical terms related to language variation. Differences between the performance of boys and girls and that of the two schools are also analysed. The paper concludes that the socio-economic context of the schools may be a more important factor than gender in variations over time identified in the data.

Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks

The themes of awareness and influence within the innovation diffusion process are addressed. The innovation diffusion process is typically represented as stages, yet awareness and influence are somewhat under-represented in the literature. Awareness and influence are situated within the contextual setting of individual actors but also within the broader institutional forces. Understanding how actors become aware of an innovation and then how their opinion is influenced is important for creating a more innovation-active UK construction sector. Social network analysis is proposed as one technique for mapping how awareness and influence occur and what they look like as a network. Empirical data are gathered using two modes of enquiry. This is done through a pilot study consisting of chartered professionals and then through a case study organization as it attempted to diffuse an innovation. The analysis demonstrates significant variations across actors’ awareness and influence networks. It is argued that social network analysis can complement other research methods in order to present a richer picture of how actors become aware of innovations and where they draw their influences regarding adopting innovations. In summarizing the findings, a framework for understanding awareness and influence associated with innovation within the UK construction sector is presented. Finally, with the UK construction sector continually being encouraged to be innovative, understanding and managing an actor’s awareness and influence network will be beneficial. The overarching conclusion thus describes the need not only to build research capacity in this area but also to push the boundaries related to the research methods employed.

Public awareness of, and attitude to, Reading's urban gardens: the findings of a questionnaire survey

This paper records and analyses the results of a questionnaire survey, undertaken in Reading in January and February 1994, into the awareness and use of Reading's town centre gardens. The results indicate that although the majority of those interviewed were aware of one or more of the gardens, relatively few visit any of the gardens and, of those who do, the majority visit infrequently. Although the gardens are generally very well liked by those who use them, no clear reasons emerge as to the motivation for visiting, beyond using them as a short cut or as a source of fresh air and tranquillity. Equally, beyond the provision of information and signposting, there appears to be little to turn current non-users into users of the gardens. The report concludes that beyond some managerial issues such as safety and cleanliness, the Borough Council needs to address the extent to which the gardens could play a more central role in the life of the town and, if this is the case, how this might be achieved.

Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe

Producing projections of future crop yields requires careful thought about the appropriate use of atmosphere-ocean global climate model (AOGCM) simulations. Here we describe and demonstrate multiple methods for ‘calibrating’ climate projections using an ensemble of AOGCM simulations in a ‘perfect sibling’ framework. Crucially, this type of analysis assesses the ability of each calibration methodology to produce reliable estimates of future climate, which is not possible just using historical observations. This type of approach could be more widely adopted for assessing calibration methodologies for crop modelling. The calibration methods assessed include the commonly used ‘delta’ (change factor) and ‘nudging’ (bias correction) approaches. We focus on daily maximum temperature in summer over Europe for this idealised case study, but the methods can be generalised to other variables and other regions. The calibration methods, which are relatively easy to implement given appropriate observations, produce more robust projections of future daily maximum temperatures and heat stress than using raw model output. The choice over which calibration method to use will likely depend on the situation, but change factor approaches tend to perform best in our examples. Finally, we demonstrate that the uncertainty due to the choice of calibration methodology is a significant contributor to the total uncertainty in future climate projections for impact studies. We conclude that utilising a variety of calibration methods on output from a wide range of AOGCMs is essential to produce climate data that will ensure robust and reliable crop yield projections.

Measuring societal awareness of the rural agrarian landscape: indicators and scale issues

The work presented in this report is part of the effort to define the landscape state and diversity indicator in the frame of COM (2006) 508 “Development of agri-environmental indicators for monitoring the integration of environmental concerns into the common agricultural policy”. The Communication classifies the indicators according to their level of development, which, for the landscape indicator is “in need of substantial improvements in order to become fully operational”. For this reason a full re-definition of the indicator has been carried out, following the initial proposal presented in the frame of the IRENA operation (“Indicator Reporting on the Integration of Environmental Concerns into Agricultural Policy”). The new proposal for the landscape state and diversity indicator is structured in three components: the first concerns the degree of naturalness, the second landscape structure, the third the societal appreciation of the rural landscape. While the first two components rely on a strong bulk of existing literature, the development of the methodology has made evident the need for further analysis of the third component, which is based on a newly proposed top-down approach. This report presents an in-depth analysis of such component of the indicator, and the effort to include a social dimension in large scale landscape assessment.