1,429 research outputs found

    Importance of long-term cycles for predicting water level dynamics in natural lakes

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    Lakes are disproportionately important ecosystems for humanity, containing 77% of the liquid surface freshwater on Earth and comprising key contributors to global biodiversity. With an ever-growing human demand for water and increasing climate uncertainty, there is pressing need for improved understanding of the underlying patterns of natural variability of water resources and consideration of their implications for water resource management and conservation. Here we use Bayesian harmonic regression models to characterise water level dynamics and study the influence of cyclic components in confounding estimation of long-term directional trends in water levels in natural Irish lakes. We found that the lakes were characterised by a common and well-defined annual seasonality and several inter-annual and inter-decadal cycles with strong transient behaviour over time. Importantly, failing to account for the longer-term cyclic components produced a significant overall underestimation of the trend effect. Our findings demonstrate the importance of contextualising lake water resource management to the specific physical setting of lakes

    "We must get in front of these blighters": Political Press Culture in the West Midlands, 1918-1925

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    This chapter seeks to challenge the current orthodoxy that a 'national' political culture had emerged by 1918 and that the provincial press failed to reflect the new, class-based politics of the period. By focusing on the experience of Birmingham and the West Midlands, it seeks to demonstrate that although national issues dominated the political debate in the area, these were refracted through the local press and played out in a regional context. The rise and fall of two local political newspapers acts as a prism for the changing political culture of the inter-war years but demonstrates that a resilient Midlands identity was present in the politics of the period

    A Transdisciplinary Approach to Water Access: An Exploratory Case Study in Indigenous Communities in Chiapas, Mexico

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    In this article, we address the water challenges faced by Indigenous communities (ICs) in the context of Sustainable Development Goal 6 (SDG 6). The importance of ICs for sustainable regional development is increasingly recognised both at, a policy level and in practice. However, there is a reported lack of empirical evidence that gives voice to how such communities perceive development, particularly sustainable water development as articulated in the United Nations Sustainable Development Goals (2015–2030). This article provides case-based evidence from one Indigenous community setting, which challenges assumptions concerning water-related development. Using a qualitative methodology, this case study explores the problem of access to safe water faced by ICs and applies a value cocreation framework based on service-dominant logic. The findings highlight the need to develop sustainable water service models focused on the provision of water not just as a commodity or resource but also as a service. Initiatives aimed at addressing water-related challenges will be more likely to succeed when the culture, experiences, knowledge and practices of the communities in need of clean water access are valued and meaningfully incorporated into value cocreation processes

    A simple principal stratum estimator for failure to initiate treatment

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    A common intercurrent event affecting many trials is when some participants do not begin their assigned treatment. For example, in a trial comparing two different methods for fluid delivery during surgery, some participants may have their surgery cancelled. Similarly, in a double-blind drug trial, some participants may not receive any dose of study medication. The commonly used intention-to-treat analysis preserves the randomisation structure, thus protecting against biases from post-randomisation exclusions. However, it estimates a treatment policy effect (i.e. addresses the question "what is the effect of the intervention, regardless of whether the participant actually begins treatment?"), which may not be the most clinically relevant estimand. A principal stratum approach, estimating the treatment effect in the subpopulation of participants who would initiate treatment (regardless of treatment arm), may be a more clinically relevant estimand for many trials. We show that a simple principal stratum estimator based on a "modified intention-to-treat" population, where participants who experience the intercurrent event are excluded, is unbiased for the principal stratum estimand under certain assumptions that are likely to be plausible in many trials, namely that participants who initiate the intervention under one treatment condition would also do so under the other treatment condition. We provide several examples of trials where this assumption is plausible, and several instances where it is not. We conclude that this simple principal stratum estimator can be a useful strategy for handling failure to initiate treatment

    Using modified intention-to-treat as a principal stratum estimator for failure to initiate treatment

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    BACKGROUND: A common intercurrent event affecting many trials is when some participants do not begin their assigned treatment. For example, in a double-blind drug trial, some participants may not receive any dose of study medication. Many trials use a 'modified intention-to-treat' approach, whereby participants who do not initiate treatment are excluded from the analysis. However, it is not clear (a) the estimand being targeted by such an approach and (b) the assumptions necessary for such an approach to be unbiased. METHODS: Using potential outcome notation, we demonstrate that a modified intention-to-treat analysis which excludes participants who do not begin treatment is estimating a principal stratum estimand (i.e. the treatment effect in the subpopulation of participants who would begin treatment, regardless of which arm they were assigned to). The modified intention-to-treat estimator is unbiased for the principal stratum estimand under the assumption that the intercurrent event is not affected by the assigned treatment arm, that is, participants who initiate treatment in one arm would also do so in the other arm (i.e. if someone began the intervention, they would also have begun the control, and vice versa). RESULTS: We identify two key criteria in determining whether the modified intention-to-treat estimator is likely to be unbiased: first, we must be able to measure the participants in each treatment arm who experience the intercurrent event, and second, the assumption that treatment allocation will not affect whether the participant begins treatment must be reasonable. Most double-blind trials will satisfy these criteria, as the decision to start treatment cannot be influenced by the allocation, and we provide an example of an open-label trial where these criteria are likely to be satisfied as well, implying that a modified intention-to-treat analysis which excludes participants who do not begin treatment is an unbiased estimator for the principal stratum effect in these settings. We also give two examples where these criteria will not be satisfied (one comparing an active intervention vs usual care, where we cannot identify which usual care participants would have initiated the active intervention, and another comparing two active interventions in an unblinded manner, where knowledge of the assigned treatment arm may affect the participant's choice to begin or not), implying that a modified intention-to-treat estimator will be biased in these settings. CONCLUSION: A modified intention-to-treat analysis which excludes participants who do not begin treatment can be an unbiased estimator for the principal stratum estimand. Our framework can help identify when the assumptions for unbiasedness are likely to hold, and thus whether modified intention-to-treat is appropriate or not
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