EEG in the diagnostics of Alzheimer’s disease

Dementia caused by Alzheimer’s disease (AD) is worldwide one of the main medical and social challenges for the next years and decades. An automated analysis of changes in the electroencephalogram (EEG) of patients with AD may contribute to improving the quality of medical diagnoses. In this paper, measures based on uni- and multi-variate spectral densities are studied in order to measure slowing and, in greater detail, reduced synchrony in the EEG signals. Hereby, an EEG segment is interpreted as sample of a (weakly) stationary stochastic process. The spectral density was computed using an indirect estimator. Slowing was considered by calculating the spectral power in predefined frequency bands. As measures for synchrony between single EEG signals, we analyzed coherences, partial coherences, bivariate and conditional Granger causality; for measuring synchrony between groups of EEG signals, we considered coherences, partial coherences, bivariate and conditional Granger causality between the respective first principal components of each group, and dynamic canonic correlations. As measure for local synchrony within a group, the amount of variance explained by the respective first principal component of static and dynamic principal component analysis was investigated. These measures were exemplarily computed for resting state EEG recordings from 83 subjects diagnosed with probable AD. Here, the severity of AD is quantified by the Mini Mental State Examination score.     

Gerechtigkeit als Politik der Befähigung zu reflexiver Selbstbestimmung

Drawing on Günter Dux’ thesis concerning the co-evolution of social development and cognitive competence, the article argues that the 21st century offers the opportunity to universalize, for the first time, a human potential deemed a general, species-typical capacity, namely the capacity to reason logically and reflexively at the levels of formal operations (Piaget) and post-conventional understandings of social order (Kohlberg). A key prerequisite for realizing this potential are enabling policies aimed at equalizing the freedom of self-determination. Once this is accepted as a central tenet of social policies, a shift in the relative priorities guiding the allocation of public welfare funds is required that broadly follows Scandinavian models. Both considerations of justice and sustainability support such a shift.     

Frontier production functions

This paper summarizes the literature on frontier production and cost functions and on their relationship to the problem of efficiency measurement.     

Designing a household survey to address seasonality in child care arrangements

In household telephone surveys, a long field period may be required to maximize the response rate and achieve adequate sample sizes. However, long field periods can be problematic when measures of seasonally affected behavior are sought. Surveys of child care use are one example because child care arrangements vary by season. Options include varying the questions posed about school-year and summer arrangements or posing retrospective questions about child care use for the school year only. This article evaluates the bias associated with the use of retrospective questions about school-year child care arrangements in the 1999 National Survey of America's Families. The authors find little evidence of bias and hence recommend that future surveys use the retrospective approach.     

Level and change of group-focused enmity in Germany: unconditional and conditional latent growth curve models with four panel waves

In this study, we investigate and explain the level and change of six elements of group-focused enmity (GFE; see Zick et al. in J. Soc. Issues 64(2):363–383, 2008) in Germany between 2002 and 2006: racism, xenophobia, anti-Semitism, homophobia, exclusion of homeless people and support for rights of the established. For the data analysis, a representative 4-year panel study of the adult non-immigrant German population collected during the years 2002–2006 is used, and the development of each GFE component is tested by using an unconditional second-order latent growth curve model (LGM) (with full information maximum likelihood, FIML). We find that the level of 5 of the 6 components (racism, xenophobia, anti-Semitism, homophobia, exclusion of homeless people) displays an increase at the beginning of the observed period followed by a decrease. However, the sixth aspect, rights of the established, displays a continuous linear increase over time. The different developmental pattern stands in contrast to Allport’s (The nature of prejudice. Perseus Books, Cambridge, 1954) hypothesis for the strong link between the components and their development over time. We try to explain this different developmental pattern by several sociodemographic characteristics. This is performed by using a conditional second-order latent growth curve model.     

An adaptive resampling scheme for cycle estimation

Bayesian dynamic linear models (DLMs) are useful in time series modelling, because of the flexibility that they off er for obtaining a good forecast. They are based on a decomposition of the relevant factors which explain the behaviour of the series through a series of state parameters. Nevertheless, the DLM as developed by West and Harrison depend on additional quantities, such as the variance of the system disturbances, which, in practice, are unknown. These are referred to here as 'hyper-parameters' of the model. In this paper, DLMs with autoregressive components are used to describe time series that show cyclic behaviour. The marginal posterior distribution for state parameters can be obtained by weighting the conditional distribution of state parameters by the marginal distribution of hyper-parameters. In most cases, the joint distribution of the hyperparameters can be obtained analytically but the marginal distributions of the components cannot, so requiring numerical integration. We propose to obtain samples of the hyperparameters by a variant of the sampling importance resampling method. A few applications are shown with simulated and real data sets.     

An experimental investigation of violations of transitivity in choice under uncertainty

Several models of decision-making imply systematic violations of transitivity of preference. Our experiments explored whether people show patterns of intransitivity predicted by regret theory and majority rule. To distinguish “true” violations from those produced by “error,” a model was fit in which each choice can have a different error rate and each person can have a different pattern of true preferences that need not be transitive. Error rate for a choice is estimated from preference reversals between repeated presentations of that same choice. Our results showed that very few people repeated intransitive patterns. We can retain the hypothesis that transitivity best describes the data of the vast majority of participants.