Reducing the Bias of Causality Measures

Measures of the direction and strength of the interdependence between two time series are evaluated and modified in order to reduce the bias in the estimation of the measures, so that they give zero values when there is no causal effect. For this, point shuffling is employed as used in the frame of surrogate data. This correction is not specific to a particular measure and it is implemented here on measures based on state space reconstruction and information measures. The performance of the causality measures and their modifications is evaluated on simulated uncoupled and coupled dynamical systems and for different settings of embedding dimension, time series length and noise level. The corrected measures, and particularly the suggested corrected transfer entropy, turn out to stabilize at the zero level in the absence of causal effect and detect correctly the direction of information flow when it is present. The measures are also evaluated on electroencephalograms (EEG) for the detection of the information flow in the brain of an epileptic patient. The performance of the measures on EEG is interpreted, in view of the results from the simulation study.Comment: 30 pages, 12 figures, accepted to Physical Review

Orthogonalized smoothing for rescaled spike and slab models

Rescaled spike and slab models are a new Bayesian variable selection method for linear regression models. In high dimensional orthogonal settings such models have been shown to possess optimal model selection properties. We review background theory and discuss applications of rescaled spike and slab models to prediction problems involving orthogonal polynomials. We first consider global smoothing and discuss potential weaknesses. Some of these deficiencies are remedied by using local regression. The local regression approach relies on an intimate connection between local weighted regression and weighted generalized ridge regression. An important implication is that one can trace the effective degrees of freedom of a curve as a way to visualize and classify curvature. Several motivating examples are presented.Comment: Published in at http://dx.doi.org/10.1214/074921708000000192 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

A Random Forests Approach to Assess Determinants of Central Bank Independence

A non-parametric efficient statistical method, Random Forests, is implemented for the selection of the determinants of Central Bank Independence (CBI) among a large database of economic, political, and institutional variables for OECD countries. It permits ranking all the determinants based on their importance in respect to the CBI and does not impose a priori assumptions on potential nonlinear relationships in the data. Collinearity issues are resolved, because correlated variables can be simultaneously considered

Determinants of Central Bank independence: a random forest approach

In this paper we implement an effcient non-parametric statistical method, Random survival forests, for the selection of the determinants of Central Bank Independence (CBI) among a large data base of political and economic variables for OECD countries.This statistical technique enables us to overcome omitted variables and overftting problems. It turns out that the economic variables are major determinants compared to the political ones and linear andnonlinear effects of chosen predictors on CBI are found

Diagnosis of Infection After Splenectomy for Trauma Should be Based on Lack of Platelets Rather Than White Blood Cell Count

Background: There is a lack of evidence-based criteria to assist the diagnosis of infection following trauma splenectomy (TS). However, the literature suggests that white blood cell count (WBC) is associated with infection in patients who undergo TS. We sought to find whether there exist key differences in laboratory and clinical parameters that can assist the diagnosis of infection after TS. Methods: We evaluated all consecutive trauma patients who had undergone TS at a Level 1 trauma center from 2005 to 2011 for the development of infection. To do this, we compared the values of demographic, laboratory, and clinical variables of infected and non-infected patients on odd post-operative days (POD) in the period from 1–15 days after TS. Results: Of 127 patients who underwent TS, 25 died within 48 h after the procedure and were excluded from our analysis, leaving, 102 patients for investigation. In the 41 (40%) patients who developed an infection, the mean day for the first infectious episode was POD 7 (range, POD 4–14). The three most common infections were pneumonia (51%), urinary tract infection (24%), and bacteremia (20%). An evaluation of laboratory and clinical parameters showed no differences in the WBC of the patients who did and did not develop infections at any time in the 15 d after TS. However, the platelet count was statistically significantly higher in non-infected patients on POD 3–9 and on POD 13, and maximal body temperature was statistically significantly higher in the infected group of patients during the first week after TS. Differences in laboratory and clinical values of the infected and non-infected patients were greatest on POD 5. Conclusions: Patients who undergo TS have high rates of infectious complications. The WBC is not a reliable predictor of infection in these patients in the 2 wks following TS. However, patients who do not develop infection after TS have statistically significantly higher absolute platelet counts and rates of change in their daily platelet counts than those who develop infection

Diagnosis of Infection After Splenectomy for Trauma Should be Based on Lack of Platelets Rather Than White Blood Cell Count

Background: There is a lack of evidence-based criteria to assist the diagnosis of infection following trauma splenectomy (TS). However, the literature suggests that white blood cell count (WBC) is associated with infection in patients who undergo TS. We sought to find whether there exist key differences in laboratory and clinical parameters that can assist the diagnosis of infection after TS. Methods: We evaluated all consecutive trauma patients who had undergone TS at a Level 1 trauma center from 2005 to 2011 for the development of infection. To do this, we compared the values of demographic, laboratory, and clinical variables of infected and non-infected patients on odd post-operative days (POD) in the period from 1–15 days after TS. Results: Of 127 patients who underwent TS, 25 died within 48 h after the procedure and were excluded from our analysis, leaving, 102 patients for investigation. In the 41 (40%) patients who developed an infection, the mean day for the first infectious episode was POD 7 (range, POD 4–14). The three most common infections were pneumonia (51%), urinary tract infection (24%), and bacteremia (20%). An evaluation of laboratory and clinical parameters showed no differences in the WBC of the patients who did and did not develop infections at any time in the 15 d after TS. However, the platelet count was statistically significantly higher in non-infected patients on POD 3–9 and on POD 13, and maximal body temperature was statistically significantly higher in the infected group of patients during the first week after TS. Differences in laboratory and clinical values of the infected and non-infected patients were greatest on POD 5. Conclusions: Patients who undergo TS have high rates of infectious complications. The WBC is not a reliable predictor of infection in these patients in the 2 wks following TS. However, patients who do not develop infection after TS have statistically significantly higher absolute platelet counts and rates of change in their daily platelet counts than those who develop infection