Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.

Potential clinical utility of polymerase chain reaction in microbiological testing for sepsis

OBJECTIVES: To evaluate the potential improvement of antimicrobial treatment by utilizing a new multiplex polymerase chain reaction (PCR) assay that identifies sepsis-relevant microorganisms in blood. DESIGN: Prospective, observational international multicentered trial. SETTING: University hospitals in Germany (n = 2), Spain (n = 1), and the United States (n = 1), and one Italian tertiary general hospital. PATIENTS: 436 sepsis patients with 467 episodes of antimicrobial treatment. METHODS: Whole blood for PCR and blood culture (BC) analysis was sampled independently for each episode. The potential impact of reporting microorganisms by PCR on adequacy and timeliness of antimicrobial therapy was analyzed. The number of gainable days on early adequate antimicrobial treatment attributable to PCR findings was assessed. MEASUREMENTS AND MAIN RESULTS: Sepsis criteria, days on antimicrobial therapy, antimicrobial substances administered, and microorganisms identified by PCR and BC susceptibility tests. RESULTS: BC diagnosed 117 clinically relevant microorganisms; PCR identified 154. Ninety-nine episodes were BC positive (BC+); 131 episodes were PCR positive (PCR+). Overall, 127.8 days of clinically inadequate empirical antibiotic treatment in the 99 BC+ episodes were observed. Utilization of PCR-aided diagnostics calculates to a potential reduction of 106.5 clinically inadequate treatment days. The ratio of gainable early adequate treatment days to number of PCR tests done is 22.8 days/100 tests overall (confidence interval 15-31) and 36.4 days/100 tests in the intensive care and surgical ward populations (confidence interval 22-51). CONCLUSIONS: Rapid PCR identification of microorganisms may contribute to a reduction of early inadequate antibiotic treatment in sepsis.

Expected and Unexpected Consequences of the Educational Expansion in Europe and the US. Theoretical approaches and empirical findings in comparative perspective

A main mechanism behind the change in European and North American societies in the second half of the 20th century is the educational expansion, i.e. the increase in educational opportunities and the higher demand for education. Whereas other abstract social processes like modernization have been widely theorized in social science literature, the educational expansion and its consequences in particular have not been well studied. Therefore the main aim of this compilation is to deal with the question of whether the demands of the educational reforms have been fulfilled and which other consequences the educational expansion has had. This book will focus on consequences of the educational expansion for individuals and their life courses as well as for the social structure and other societal areas such as culture and politics. Aspects that will be analysed in the light of educational expansion include participation in education, educational inequalities, labour market outcomes, educational returns, and gender differences as well as crime, life expectancy, and lifestyles. Countries analysed in the book include West European countries like Germany, France, Italy and Spain, East European countries (Hungary, Poland, and the Czech Republic) as well as the US.

Expected performance of the ATLAS experiment - detector, trigger and physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN.

Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.