Statistics for Studies of Human Welfare

Developments in the recent past have substantially increased our ability to measure, compute, and communicate. We take the view that a corresponding improved understanding of processes in the life sciences will come about only through more intensive studies of properties of statistical methods and algorithms and transparent, open source computing environments.     

Causality: a Statistical View

Statistical aspects of causality are reviewed in simple form and the impact of recent work discussed. Three distinct notions of causality are set out and implications for densities and for linear dependencies explained. The importance of appreciating the possibility of effect modifiers is stressed, be they intermediate variables, background variables or unobserved confounders. In many contexts the issue of unobserved confounders is salient. The difficulties of interpretation when there are joint effects are discussed and possible modifications of analysis explained. The dangers of uncritical conditioning and marginalization over intermediate response variables are set out and some of the problems of generalizing conclusions to populations and individuals explained. In general terms the importance of search for possibly causal variables is stressed but the need for caution is emphasized.     

On the Application of Conditional Independence to Ordinal Data

A special log linear parameterization is described for contingency tables which exploits prior knowledge that an ordinal scale of the variables is involved. It is helpful, in particular, in guiding the possible merging of adjacent levels of variables and may simplify interpretation if higher-order interactions are present. Several sets of data are discussed to illustrate the types of interpretation that can be achieved. The simple structure of the maximum likelihood estimates is derived by use of Lagrange multipliers.     

The German economy in 1982 and beyond

The Federal Republic of Germany is presently experiencing the deepest and longest recession in its history. The situation is characterised by high and rising unemployment figures, slowing growth, a steep increase in the number of bankruptcies in the business sector as well as by a rapidly rising public sector deficit. They key to any solution, Dr. Wermuth argues, is held by the German monetary authorities more than by anyone else.     

Traceable Regressions

In this paper, we define and study the concept of traceable regressions and apply it to some examples. Traceable regressions are sequences of conditional distributions in joint or single responses for which a corresponding graph captures an independence structure and represents, in addition, conditional dependences that permit the tracing of pathways of dependence. We give the properties needed for transforming these graphs and graphical criteria to decide whether a path in the graph induces a dependence. The much stronger constraints on distributions that are faithful to a graph are compared to those needed for traceable regressions.