Individual Differences in Infant Skills as Predictors of Child-Caregiver Joint Attention and Language

Current research suggests that the extent to which child-caregiver dyads engage in interactions involving episodes of joint or coordinated attention can have a significant impact on early lexical acquisition. In this regard it has been recognized that individual differences in early developing child communication skills, such as capacity to follow gaze and early infant language, may contribute to these child-caregiver interactional patterns, as well as to subsequent language development. To address this expectation, 21 infant-parent dyads were recruited for participation in a longitudinal study. Early infant language, responding to joint attention skill, and cognitive development were assessed at 12 months of age. Child-caregiver joint attention episodes, as well as responding to joint attention skill and child language, were assessed at 18 months of age. Developmental outcome, using the MacArthur Communicative Development Inventories and the Bayley Scales of Infant Development-II, was assessed at 21 and 24 months of age. Consistent with previous findings, results indicated that individual differences in child-caregiver episodes of joint attention were related to language at 18 months. In addition, though, 12 month vocabulary and responding to joint attention skill were associated with some aspects of 18 month child-caregiver interaction, as well as subsequent language development. In general, 12 month child measures and 18 month child-caregiver interaction measures appeared to make unique contributions to language development in this sample. These results suggest the need to further consider the role of infant skills in the connections between child-caregiver joint attention episodes and language development.     

Organization and Supply of Long‐term Care Services for the Elderly: A Bird's‐eye View of Old and New EU Member States

This article provides an overview of the organization of formal long‐term care (LTC) systems for the elderly in ten old and 11 new EU member states (MS). Generally, we find that the main responsibility for regulating LTC services is centralized in half of these countries, whereas in the remaining countries, this responsibility is typically shared between authorities at the central level and those at the regional or local levels in both institutional and home‐based care. Responsibilities for planning LTC capacities are jointly met by central and non‐central authorities in most countries. Access to publicly financed services is rarely means tested, and most countries have implemented legal entitlements conditional on needs. In virtually all countries, access to institutional care is subject to cost sharing, which also applies to home‐based care in most countries. The relative importance of institutional LTC relative to home‐based LTC services differs significantly across Europe. Although old MS appear to be experiencing some degree of convergence, institutional capacity levels still span a wide range. Considerable diversity may also be observed in the national public–private mix in the provision of LTC services. Lastly, free choice between public and private providers exists in the vast majority of these countries. This overview provides vital insights into the differences and similarities in the organization of LTC systems across Europe, especially between old and new MS, while also contributing valuable insight into previously neglected topics, thus broadening the knowledge base of international experience for mutual learning.     

Die Mehrebenen-Analyse. Ihre praktische Anwendung und theoretische Annahmen

Multilevel analysis has become more common during the last ten years. A reason might be that this method allows us to analyse micro- and macro relationships in one step. Loosely, one can characterize it as a combination of variance analysis and regression analysis. Nevertheless, questions occur frequently concerning its practical application, the statistical requirements, the differences to OLS-Regression, and so on. Answering these questions, this paper has two particular aims. The first aim is to show the practical use and to give an idea of the possibilities of this method. The second aim is to discuss statistical requirements and frequently asked questions. For this purpose the application of a two level regression is illustrated by using data from ISSP and analysing the perception of vertical conflicts in an international view. This paper starts with a practical application. The random intercept model is discussed, where the intercepts vary among macro units and therefore regression lines run at different levels. Afterwards a random slope model is shown. Here, the regression coefficients also vary among countries. Among these practical applications other topics are discussed, e. g. model fit, minimum sample size, explained variance, estimation-methods, and standardisation of coefficients. Finally there is given a brief overview of this method and different software programs.     

Maximum Test versus Adaptive Tests for the Two-Sample Location Problem

For the non-parametric two-sample location problem, adaptive tests based on a selector statistic are compared with a maximum and a sum test, respectively. When the class of all continuous distributions is not restricted, the sum test is not a robust test, i.e. it does not have a relatively high power across the different possible distributions. However, according to our simulation results, the adaptive tests as well as the maximum test are robust. For a small sample size, the maximum test is preferable, whereas for a large sample size the comparison between the adaptive tests and the maximum test does not show a clear winner. Consequently, one may argue in favour of the maximum test since it is a useful test for all sample sizes. Furthermore, it does not need a selector and the specification of which test is to be performed for which values of the selector. When the family of possible distributions is restricted, the maximin efficiency robust test may be a further robust alternative. However, for the family of t distributions this test is not as powerful as the corresponding maximum test.     

Individuelle und kontextuelle Determinanten der Teilhabe an Sozialkapital

We ask for conditions influencing membership in social organizations as strongholds of social capital. Beside individual characteristics, contextual factors such as political, social, or economic settings are also taken into consideration to explain individual decisions to participate in social organizations. The influences of individual and contextual level factors are tested simultaneously in several multi-level analyses. The results show that membership in social associations on the one hand is affected by individual characteristics such as marked trust in others, high level of education, church attendance, strong ties with the neighbourhood, age and sex, and on the other hand by contextual factors such as a catholic social context and institutional settings. In particular, Swiss direct democracy offering larger possibilities of participation facilitates membership in social organizations.     

Item nonresponse on income questions in panel surveys: Incidence, imputation and the impact on inequality and mobility

Summary: This paper deals with item nonresponse on income questions in panel surveys and with longitudinal and cross–sectional imputation strategies to cope with this phenomenon. Using data from the German SOEP, we compare income inequality and mobility indicators based only on truly observed information to those derived from observed and imputed observations. First, we find a positive correlation between inequality and imputation. Secondly, income mobility appears to be significantly understated using observed information only. Finally, longitudinal analyses provide evidence for a positive inter–temporal correlation between item nonresponse and any kind of subsequent nonresponse.* We are grateful to two anonymous referees and to Jan Goebel for very helpful comments and suggestions on an earlier draft of this paper. The paper also benefited from discussions with seminar participants at the Workshop on Item Nonresponse and Data Quality in Large Social Surveys, Basel/CH, October 9–11, 2003.     

Bayesian predictive power: choice of prior and some recommendations for its use as probability of success in drug development

Bayesian predictive power, the expectation of the power function with respect to a prior distribution for the true underlying effect size, is routinely used in drug development to quantify the probability of success of a clinical trial. Choosing the prior is crucial for the properties and interpretability of Bayesian predictive power. We review recommendations on the choice of prior for Bayesian predictive power and explore its features as a function of the prior. The density of power values induced by a given prior is derived analytically and its shape characterized. We find that for a typical clinical trial scenario, this density has a u‐shape very similar, but not equal, to a β‐distribution. Alternative priors are discussed, and practical recommendations to assess the sensitivity of Bayesian predictive power to its input parameters are provided. Copyright © 2016 John Wiley & Sons, Ltd.     

Inference for Multi‐dimensional High‐frequency Data with an Application to Conditional Independence Testing

We find the asymptotic distribution of the multi‐dimensional multi‐scale and kernel estimators for high‐frequency financial data with microstructure. Sampling times are allowed to be asynchronous and endogenous. In the process, we show that the classes of multi‐scale and kernel estimators for smoothing noise perturbation are asymptotically equivalent in the sense of having the same asymptotic distribution for corresponding kernel and weight functions. The theory leads to multi‐dimensional stable central limit theorems and feasible versions. Hence, they allow to draw statistical inference for a broad class of multivariate models, which paves the way to tests and confidence intervals in risk measurement for arbitrary portfolios composed of high‐frequently observed assets. As an application, we enhance the approach to construct a test for investigating hypotheses that correlated assets are independent conditional on a common factor.