Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

Welfare provision in Sweden and the dominant position of the Sap

There have been almost fifty years since Harry Eckstein' s classic monograph, A Theory of Stable Democracy (Princeton, 1961), where he sketched out the basic tenets of the “congruence theory”, which was to become one of the most important and innovative contributions to understanding democratic rule. His next work, Division and Cohesion in Democracy, (Princeton University Press: 1966) is designed to serve as a plausibility probe for this 'theory' (ftn.) and is a case study of a Northern democratic system, Norway. What is more, this line of his work best exemplifies the contribution Eckstein brought to the methodology of comparative politics through his seminal article, “ “Case Study and Theory in Political Science” ” (in Greenstein and Polsby, eds., Handbook of Political Science, 1975), on the importance of the case study as an approach to empirical theory. This article demonstrates the special utility of “crucial case studies” in testing theory, thereby undermining the accepted wisdom in comparative research that the larger the number of cases the better. Although not along the same lines, but shifting the case study unit of research, I intend to take up here the challenge and build upon an equally unique political system, the Swedish one. Bearing in mind the peculiarities of the Swedish political system, my unit of analysis is going to be further restricted to the Swedish Social Democratic Party, the Svenska Arbetare Partiet. However, my research stays within the methodological framework of the case study theory inasmuch as it focuses on a single political system and party. The Swedish SAP endurance in government office and its electoral success throughout half a century (ftn. As of the 1991 election, there were about 56 years - more than half century - of interrupted social democratic "reign" in Sweden.) are undeniably a performance no other Social Democrat party has yet achieved in democratic conditions. Therefore, it is legitimate to inquire about the exceptionality of this unique political power combination. Which were the different components of this dominance power position, which made possible for SAP's governmental office stamina? I will argue here that it was the end-product of a combination of multifarious factors such as a key position in the party system, strong party leadership and organization, a carefully designed strategy regarding class politics and welfare policy. My research is divided into three main parts, the historical incursion, the 'welfare' part and the 'environment' part. The first part is a historical account of the main political events and issues, which are relevant for my case study. Chapter 2 is devoted to the historical events unfolding in the 1920-1960 period: the Saltsjoebaden Agreement, the series of workers' strikes in the 1920s and SAP's inception. It exposes SAP's ascent to power in the mid 1930s and the party's ensuing strategies for winning and keeping political office, that is its economic program and key economic goals. The following chapter - chapter 3 - explores the next period, i.e. the period from 1960s to 1990s and covers the party's troubled political times, its peak and the beginnings of the decline. The 1960s are relevant for SAP's planning of a long term economic strategy - the Rehn Meidner model, a new way of macroeconomic steering, based on the Keynesian model, but adapted to the new economic realities of welfare capitalist societies. The second and third parts of this study develop several hypotheses related to SAP's 'dominant position' (endurance in politics and in office) and test them afterwards. Mainly, the twin issues of economics and environment are raised and their political relevance for the party analyzed. On one hand, globalization and its spillover effects over the Swedish welfare system are important causal factors in explaining the transformative social-economic challenges the party had to put up with. On the other hand, Europeanization and environmental change influenced to a great deal SAP's foreign policy choices and its domestic electoral strategies. The implications of globalization on the Swedish welfare system will make the subject of two chapters - chapters four and five, respectively, whereupon the Europeanization consequences will be treated at length in the third part of this work - chapters six and seven, respectively. Apparently, at first sight, the link between foreign policy and electoral strategy is difficult to prove and uncanny, in the least. However, in the SAP's case there is a bulk of literature and public opinion statistical data able to show that governmental domestic policy and party politics are in a tight dependence to foreign policy decisions and sovereignty issues. Again, these country characteristics and peculiar causal relationships are outlined in the first chapters and explained in the second and third parts. The sixth chapter explores the presupposed relationship between Europeanization and environmental policy, on one hand, and SAP's environmental policy formulation and simultaneous agenda-setting at the international level, on the other hand. This chapter describes Swedish leadership in environmental policy formulation on two simultaneous fronts and across two different time spans. The last chapter, chapter eight - while trying to develop a conclusion, explores the alternative theories plausible in explaining the outlined hypotheses and points out the reasons why these theories do not fit as valid alternative explanation to my systemic corporatism thesis as the main causal factor determining SAP's 'dominant position'. Among the alternative theories, I would consider Traedgaardh L. and Bo Rothstein's historical exceptionalism thesis and the public opinion thesis, which alone are not able to explain the half century social democratic endurance in government in the Swedish case.

Testing future weak lensing surveys through simulations of observations

Weak lensing experiments such as the future ESA-accepted mission Euclid aim to measure cosmological parameters with unprecedented accuracy. It is important to assess the precision that can be obtained in these measurements by applying analysis software on mock images that contain many sources of noise present in the real data. In this Thesis, we show a method to perform simulations of observations, that produce realistic images of the sky according to characteristics of the instrument and of the survey. We then use these images to test the performances of the Euclid mission. In particular, we concentrate on the precision of the photometric redshift measurements, which are key data to perform cosmic shear tomography. We calculate the fraction of the total observed sample that must be discarded to reach the required level of precision, that is equal to 0.05(1+z) for a galaxy with measured redshift z, with different ancillary ground-based observations. The results highlight the importance of u-band observations, especially to discriminate between low (z < 0.5) and high (z ~ 3) redshifts, and the need for good observing sites, with seeing FWHM < 1. arcsec. We then construct an optimal filter to detect galaxy clusters through photometric catalogues of galaxies, and we test it on the COSMOS field, obtaining 27 lensing-confirmed detections. Applying this algorithm on mock Euclid data, we verify the possibility to detect clusters with mass above 10^14.2 solar masses with a low rate of false detections.

Power Transient Analysis of Experimental Devices for Jules Horowitz Material Testing Reactor (JHR)

The objective of this thesis is the power transient analysis concerning experimental devices placed within the reflector of Jules Horowitz Reactor (JHR). Since JHR material testing facility is designed to achieve 100 MW core thermal power, a large reflector hosts fissile material samples that are irradiated up to total relevant power of 3 MW. MADISON devices are expected to attain 130 kW, conversely ADELINE nominal power is of some 60 kW. In addition, MOLFI test samples are envisaged to reach 360 kW for what concerns LEU configuration and up to 650 kW according to HEU frame. Safety issues concern shutdown transients and need particular verifications about thermal power decreasing of these fissile samples with respect to core kinetics, as far as single device reactivity determination is concerned. Calculation model is conceived and applied in order to properly account for different nuclear heating processes and relative time-dependent features of device transients. An innovative methodology is carried out since flux shape modification during control rod insertions is investigated regarding the impact on device power through core-reflector coupling coefficients. In fact, previous methods considering only nominal core-reflector parameters are then improved. Moreover, delayed emissions effect is evaluated about spatial impact on devices of a diffuse in-core delayed neutron source. Delayed gammas transport related to fission products concentration is taken into account through evolution calculations of different fuel compositions in equilibrium cycle. Provided accurate device reactivity control, power transients are then computed for every sample according to envisaged shutdown procedures. Results obtained in this study are aimed at design feedback and reactor management optimization by JHR project team. Moreover, Safety Report is intended to utilize present analysis for improved device characterization.