Two proposal tips
We write a fair number of research proposals, with most of them going to the National Institutes of Health, and the Centers for Disease Control and surveillance. We also submit proposals to the National Science Foundation and NASA. For those researchers who are new to a proposal writing role here are a couple tips.
One of the first things to do after identifying the next “Big Idea” is to assess its potential viability and impact. Two items top the list. The first is the priority in terms of disease targeted; it is much easier to obtain funding for a disease with a large human and economic impact. One resource that may be of use is the global burden of disease, and of years of life lost (YYL). This article, published recently in The Lancet provides estimates from around the globe for both chronic and infectious disease burdens.
Second, if you are looking for funding in the U.S. it is important to consider what the funding organization’s budget and plan are for the near term. Remember the reviewers may not even be aware of the funding organizations research priorities. For NIH, the reviewers are external, and it is good proposal practice to remind them of the relevant NIH research priorities. A good portion of BioMedware’s research portfolio has been funded by the National Cancer Institute. Our 2015 proposals likely will incorporate information from NCI’s 2016 budget proposal and plan, which may be found here.
In summary, the message is to (1) seek to address important diseases, where importance is defined by human and economic costs; and (2) go after those proposal ideas that are highly relevant to the funding organization’s mission and budget plan.
Save the Date: April 13-14, 2015
Organized by The Cancer Prevention Institute of California and Zero Breast Cancer
Location: The California Endowment, 1111 Broadway, Oakland, CA
Geoffrey Jacquez, PhD, President of BioMedware, and Keynote speaker is conducting the preconference workshop on April 13th, titled “Space Time Analysis Using SpaceStat”.
In the news: SpaceStat for spatial analysis
Recently published articles demonstrating how SpaceStat’s rigorous, statistical analysis methods are being utilized by researchers.
Timothy S. Hare, Chad Wells, Nicole Johnson; Morehead State University, Morehead, KY, USA
International Journal of Applied Geospatial Research, 5(4), 35-53, October-December 2014 35
“…We use ESRI’s ArcGIS for data processing and visualization and BioMedware’s SpaceStat for EDA, ESDA, OLS regression, spatial regression, and GWR. SpaceStat is a set of software tools for conducting a variety of spatial statisti¬cal analysis techniques (BioMedware, 2012). It supports dynamic and interactive analysis of linked tables, charts, and maps. SpaceStat calculates probability values (p-values) for observed test statistics by comparing them to their null distributions, which estimates the likelihood of the observed values in comparison with the null distribution. The spatial weights matrix used is queen’s case contiguity.”
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Alessandro Zini, Sergio Grauso, Vladimiro Verrubbi, Luca Falconi, Gabriele Leoni, Claudio Puglisi
Landslides, DOI 10.1007/s10346-014-0515-8
Received: 25 September 2013; Accepted: 14 August 2014
Background. Debris flows represent dangerous occurrences in many parts of the world. Several disasters are documented due to this type of fast-moving landslides, therefore, natural-hazard assessment of debris flows is crucial for safety of life and property. In this paper we investigated the effectiveness of the soil erosion index as debris flows susceptibility indicator. The relation between the erosion index, which was assessed by means of the Revised Universal Soil Loss Equation (RUSLE) model, and the inventory of debris flows that have occurred in an area in Sicily was investigated.
Method. To this aim, a geographically weighted logistic regression analysis (GWR) was carried out making use of SpaceStat. While traditional logistic regression aims to obtain an average parameter estimate over the whole territory under observation, the GWR attempts to gain point-to-point estimates. Moreover, the GWR technique may provide a better fit with experimental data.
Results. The results of the statistical analysis prove the existence of a significant connection between the observed debris flows and the RUSLE erosion index. Secondly, the complexity of the GWR model, based on non-fixed regression coefficients, points out that the same value of RUSLE index can have different effects in different locations. This result highlights the behavior of complex land systems in the real world, where different forces are acting (rain, running waters, internal water pressures, internal strains, gravity, etc.) and determine different point-to-point degrees of susceptibility to debris flows. On the basis of GWR parameters a scenario analysis regarding the area was conducted.
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Follow Geoffrey Jacquez, PhD, on Twitter @GeoffJacquez.