BayesProject: Fast computation of a projection direction for multivariate changepoint detection

Statistics and Computing - This article focuses on the challenging problem of efficiently detecting changes in mean within multivariate data sequences. Multivariate changepoints can be detected by...     

Randomized response techniques for complex survey designs

Singh et al. ([13]) pointed out that the Randomized response (RR) technique proposed by Moors ([9]) is not desirable because it fails to protect the confidentiality of the respondents and they provided two alternative strategies free from the above drawback but limited to SRSWOR sampling only. In this paper, generalization of one of the strategies is provided for complex survey designs, wider class of estimators and for quantitative characteristics. Relative efficiency of the modified strategy is tested through empirical investigations. An erratum to this article is available at .     

Modernisierungstheorie und Wandel der Weltgesellschaft

The modernization and industrialization of the developing countries, especially in Asia and Latin America in the last 30 years, are facts that seem to contradict to the basic assumptions of the ruling sociological theories of development. The rise of the developing countries is a main part of the process called “globalization”. The different parts of the world are getting closer to each other by trade, industrial investments, tourism, political influences and co-operations on different levels. Theories of dependence and similar approaches don’t fit these social developments and seem to have gotten a status of falsified, refused, neglected or simply forgotten theories. “Sociological Theory” is till this day not ready to answer the open questions and to fill the scientific gap. The article shows that the classical theory of modernization is capable to describe and explain the process of modernization not only in Europe but also in the developing countries. Modernization theory is the central and encompassing theory of development, no matter whether Europe in the last 200 years, the present-day developing countries or processes of globalization is the chosen and focused subject of research activities.     

Same same but different: managerial influences on organisational performance in foundations and associations

In the last few years the management orientation of nonprofit organisation (NPOs) has been gaining importance. Management is said to have made the organisation of NPOs more effective and efficient. However, the influence of the institutional settings is often neglected in nonprofit management literature. By using a quantitative empirical approach this study investigates the influence of the legal type of Swiss nonprofits on the relationship between management dimensions and organisational performance. The research findings reveal significant differences in the management of foundations and associations. In particular, foundations have a competitive advantage in terms of innovation and market orientation. Whereas associations profit from investing in governance issues.     

MEASURING THE INTERDEPENDENCE OF MULTINATIONAL FIRMS' FOREIGN INVESTMENTS

Earlier work found evidence for geographic linkages of aggregate foreign direct investment across countries and country‐pairs. From a theoretical point of view, such linkages at the macroeconomic level may root in between‐firm as well as within‐firm linkages and originate from information spillovers across or within firms in exploring unknown markets, and vertical linkages between production plants across different locations within the firm. We use data on the universe of German multinational enterprises (MNEs) to empirically explore how marginal investments at one foreign affiliate depend on investments at other affiliates within the same MNE. The empirical approach employs two channels or modes of cross‐affiliate interdependence: mere geography (capturing horizontal linkages through correlated learning and horizontal competition within the firm) and input–output relationships within or across industries (which capture vertical linkages). Adding to earlier findings at the aggregate level, we find evidence of a significant interdependence of investments within the firm. In the firm‐level data at hand, vertical linkages appear to be more important than horizontal ones. Investments at one location tend to stimulate investments at other locations of the same MNE, particularly if input linkages are strong. The opposite seems to be true for output linkages. Beyond vertical linkages, mere geographic proximity matters only to a minor extent. This suggests that evidence of linkages through geographic closeness at aggregate data levels accrue mainly to reasons of vertical linkages within networks of affiliates. (JEL C31, D22, F21, F23, F68, G31, H32)     

Consistent Probabilistic Social Choice

Two fundamental axioms in social choice theory are consistency with respect to a variable electorate and consistency with respect to components of similar alternatives. In the context of traditional non‐probabilistic social choice, these axioms are incompatible with each other. We show that in the context of probabilistic social choice, these axioms uniquely characterize a function proposed by Fishburn (1984). Fishburn's function returns so‐called maximal lotteries, that is, lotteries that correspond to optimal mixed strategies in the symmetric zero‐sum game induced by the pairwise majority margins. Maximal lotteries are guaranteed to exist due to von Neumann's Minimax Theorem, are almost always unique, and can be efficiently computed using linear programming.     

Implementing Monte Carlo tests with p-value buckets

Software packages usually report the results of statistical tests using p-values. Users often interpret these values by comparing them with standard thresholds, for example, 0.1, 1, and 5%, which is sometimes reinforced by a star rating (***, **, and *, respectively). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, for example, by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals that cover [0, 1] and that can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations.     

Applying competing risks regression models: an overview

In many clinical research applications the time to occurrence of one event of interest, that may be obscured by another??so called competing??event, is investigated. Specific interventions can only have an effect on the endpoint they address or research questions might focus on risk factors for a certain outcome. Different approaches for the analysis of time-to-event data in the presence of competing risks were introduced in the last decades including some new methodologies, which are not yet frequently used in the analysis of competing risks data. Cause-specific hazard regression, subdistribution hazard regression, mixture models, vertical modelling and the analysis of time-to-event data based on pseudo-observations are described in this article and are applied to a dataset of a cohort study intended to establish risk stratification for cardiac death after myocardial infarction. Data analysts are encouraged to use the appropriate methods for their specific research questions by comparing different regression approaches in the competing risks setting regarding assumptions, methodology and interpretation of the results. Notes on application of the mentioned methods using the statistical software R are presented and extensions to the presented standard methods proposed in statistical literature are mentioned.