Measuring Confidentiality Risks in Census Data

Two trends have been on a collision course over the recent past. The first is the increasing demand by researchers for greater detail and flexibility in outputs from the decennial Census of Population. The second is the need felt by the Census Offices to demonstrate more clearly that Census data have been explicitly protected from the risk of disclosure of information about individuals. To reconcile these competing trends the authors propose a statistical measure of risks of disclosure implicit in the release of aggregate census data. The ideas of risk measurement are first developed for microdata where there is prior experience and then modified to measure risk in tables of counts. To make sure that the theoretical ideas are fully expounded, the authors develop small worked example. The risk measure purposed here is currently being tested out with synthetic and a real Census microdata. It is hoped that this approach will both refocus the census confidentiality debate and contribute to the safe use of user defined flexible census output geographies

The next steps in improving the outcomes of advanced ovarian cancer

Worldwide ovarian cancer affects over 200,000 women per year. Overall survival rates are poor due to two predominate reasons. First, the majority of patients present with advanced disease creating significant difficulty with effecting disease eradication. Second, acquisition of chemotherapy resistance results in untreatable progressive disease. Advances in treatment of advanced ovarian cancer involve a spectrum of interventions including improvements in frontline debulking surgery and combination chemotherapy. Anti-angiogenic factors have been shown to have activity in frontline and recurrent disease while novel chemotherapeutic agents and targeted treatments are in development particularly for disease that is resistant to platinum-based chemotherapy. These developments aim to improve the progression-free and overall survival of women with advanced ovarian cancer

Research Notes: Single seed selection for carbohydrate content in soybean seeds

We have investigated the feasibility of using single seed selection to change the sugar content of soybeans. In order to study the distribution of sucrose, raffinose, stachyose, and total sugar in the embryo, seeds of the varieties \u27Jogun\u27 and \u27Hokkaido\u27 were sliced into three portions of approximate equal weights. Slices were made parallel to the root-shoot axis with Position I containing the root-shoot axis and Position III lying distal from it

Areal interpolation and the UK’s referendum on EU membership

I show how results from the United Kingdom’s referendum on membership of the European Union can be remapped from local authority level to parliamentary constituency level through the use of a scaled Poisson regression model which incorporates demographic information from lower level geographies. I use these estimates to show how the geographic distribution of signatures to a petition for a second referendum was strongly associated with how constituencies voted in the actual referendum

Multi density DBSCAN

Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases.DBSCAN clustering algorithm relying on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN requires only one input parameter and supports the user in determining an appropriate value for it. DBSCAN cannot find clusters based on difference in densities. We extend the DBSCAN algorithm so that it can also detect clusters that differ in densities and without the need to input the value of Eps because our algorithm can find the appropriate value for each cluster individually by replacing Eps by Local

Applications of Population Counts Based on Administrative Data at Local Level

The House of Commons Treasury Committee (2008) identified the three main purposes of population statistics as resource allocation, population ratios and local planning and intelligence, and described current population estimates as ‘unfit for purpose’. This paper considers the limitations of current population statistics in the context of these purposes and how using administrative data available at local authority level can overcome them. A sequel to a companion paper in this journal dealing with the population counting methodology, it considers how administrative data can be captured and organised at a local level for the benefit of local service providers and communities. A detailed example based on one London local authority shows the results of this approach in applications related to the three purposes given. A concluding section reflects on the wider applicability of the approach

Research notes: Sterility mutants in soybeans

In 1975 we selected green, partially sterile plants in farmers\u27 fields when the normal plants had dropped their leaves and were ready for harvest . Seeds were harvested from the off-type plants and planted in the greenhouse (1975-76). The resulting plants which we called F1\u27s were nonnal

Cardiovascular Risk Factors In Middle-Aged Men In 24 Towns

Abstract included in text