Uppsala University

About: Uppsala University is a education organization based out in Uppsala, Sweden. It is known for research contribution in the topics: Population & Gene. The organization has 36485 authors who have published 107509 publications receiving 4220668 citations. The organization is also known as: Uppsala universitet & uu.se.

Hypertension and Associated Metabolic Abnormalities — The Role of Insulin Resistance and the Sympathoadrenal System

Abstract: Abnormalities of glucose, insulin, and lipoprotein metabolism are common in patients with hypertension. These changes can also be discerned in normotensive first-degree relatives of hypertensive patients. They are not present in patients with secondary forms of hypertension, do not necessarily improve when blood pressure is lowered pharmacologically, and may even be made worse by some forms of antihypertensive treatment. These metabolic abnormalities may play a part in both the pathogenesis and the complications of hypertension in many patients. We hypothesize that the metabolic abnormalities are linked to the hypertension by a pathophysiologic process that involves the sympathoadrenal system and exerts . . .

The Elusive Concept of Localization Economies: Towards a Knowledge-Based Theory of Spatial Clustering

Abstract: A number of possible advantages of industry agglomeration—or spatial clustering—have been identified in the research literature, notably those related to shared costs for infrastructure, the build-up of a skilled labour force, transaction efficiency, and knowledge spillovers leading to firm learning and innovation. We identify two shortcomings of existing research on the clustering phenomenon. First, the abundance of theoretical concepts and explanations stands in sharp contrast with the general lack of work aimed at validating these mechanisms empirically and the contradictory evidence found in recent empirical work in the field. Second, there is still a lack of a unified theoretical framework for analyzing spatial clustering. In an attempt to remedy the latter shortcoming, this paper investigates the nature of the cluster from a knowledge-creation or learning perspective. We argue for the need to establish a specific theory of the cluster where learning occupies centre stage. The basic requirements for ...

Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable

Abstract: We consider a model in which one observes multiple indicators and multiple causes of a single latent variable. In terms of the multivariate regression of the indicators on the causes, the model implies restrictions of two types: (i) the regression coefficient matrix has rank one, (ii) the residual variance-covariance matrix satisfies a factor analysis model with one common factor. The first type of restriction is familiar to econometricians and the second to psychometricians. We derive the maximum-likelihood estimators and their asymptotic variance-covariance matrix. Two alternative “limited information” estimators are also considered and compared with the maximum-likelihood estimators in terms of efficiency.

Spatial disease clusters: detection and inference.

Abstract: We present a new method of detection and inference for spatial clusters of a disease. To avoid ad hoc procedures to test for clustering, we have a clearly defined alternative hypothesis and our test statistic is based on the likelihood ratio. The proposed test can detect clusters of any size, located anywhere in the study region. It is not restricted to clusters that conform to predefined administrative or political borders. The test can be used for spatially aggregated data as well as when exact geographic co-ordinates are known for each individual. We illustrate the method on a data set describing the occurrence of leukaemia in Upstate New York.