Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

Schediasma historico philologicum de Judaeorum Pseudo-Messias

per Johannem `a Lent

Applications of random set theory in econometrics

In recent years, the econometrics literature has shown a growing interest in the study of partially identified models, in which the object of economic and statistical interest is a set rather than a point. The characterization of this set and the development of consistent estimators and inference procedures for it with desirable properties are the main goals of partial identification analysis. This review introduces the fundamental tools of the theory of random sets, which brings together elements of topology, convex geometry, and probability theory to develop a coherent mathematical framework to analyze random elements whose realizations are sets. It then elucidates how these tools have been fruitfully applied in econometrics to reach the goals of partial identification analysis.

Evaluation of an esophageal Doppler probe for the identification of experimental pseudo-electromechanical dissociation: a preliminary study

STUDY OBJECTIVE To determine the effectiveness of an esophageal doppler device to non-invasively detect experimental pseudo-electromechanical dissociation (pseudo-EMD). DESIGN Prospective, controlled, laboratory investigation using an asphyxial canine cardiac arrest model and a newly-developed esophageal flat-flow probe doppler unit. INTERVENTIONS Mongrel dogs (20) were instrumented for hemodynamic monitoring. The esophageal doppler probe was placed in the distal esophagus of each animal. Electromechanical dissociation (EMD) was induced by clamping the endotracheal tube. MEASUREMENTS AND MAIN RESULTS A period of pseudo-EMD was defined as the time where cardiac contractility was present, measured by a micromanometer tipped thoracic aortic catheter, without concurrent femoral pulses by palpation. The pseudo-EMD period could be produced consistently in all 20 animals. The characteristic doppler flow sounds were easily heard using the esophageal device in all animals. The time from endotracheal tube clamping until loss of femoral pulses was 622 +/- 96 s; until loss of radial artery doppler signals was 616 +/- 92 s; until loss of esophageal doppler signals was 728 +/- 88 s; and until loss of aortic fluctuations by thoracic aortic catheter was 728 +/- 82 s. The times to loss of esophageal doppler sounds and loss of aortic fluctuations were not significantly different. However, they were significantly longer than the time to loss of femoral pulses (P < 0.02). CONCLUSIONS The canine asphyxial EMD model can be used for short experimental studies of pseudo-EMD. Pseudo-EMD can be consistently and non-invasively detected with this esophageal doppler device. The device is as reliable as a micromanometer tipped aortic arch catheter in detecting pseudo-EMD. The doppler device could potentially be useful in improving recognition of near cardiac arrest in pre-hospital and emergency department settings. Further research on the utility of this device in other models of low-flow states should be performed.

Analecta philologico-historica, quae Judaeorum aliquot rabbinos, Pseudo-Christos conversos et proselytos eorundemque scripta et facta itemque Eliam venturum breviter recensent et describunt

studio Mich. Burchardi

Campylobacter concisus pseudo-outbreak caused by improved culture conditions.

An unusual increase of Campylobacter concisus in stool cultures provoked an outbreak investigation at the University Hospital of Bern. No epidemiological links were found between cases, and the Campylobacter isolates were clonally unrelated. A change in culture conditions to a hydrogen-rich atmosphere enhancing growth of C. concisus was deemed responsible for this pseudo-outbreak.

Saddlepoint approximations to sensitivities of tail probabilities of random sums and comparisons with Monte Carlo estimators

This article proposes computing sensitivities of upper tail probabilities of random sums by the saddlepoint approximation. The considered sensitivity is the derivative of the upper tail probability with respect to the parameter of the summation index distribution. Random sums with Poisson or Geometric distributed summation indices and Gamma or Weibull distributed summands are considered. The score method with importance sampling is considered as an alternative approximation. Numerical studies show that the saddlepoint approximation and the method of score with importance sampling are very accurate. But the saddlepoint approximation is substantially faster than the score method with importance sampling. Thus, the suggested saddlepoint approximation can be conveniently used in various scientific problems.

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.