Mapping the regional transition to cyclicity inClethrionomys rufocanus: Spectral densities and functional data analysis

We study the regional transitions in dynamics of the gray-sided vole,Clethrionomys rufocanus, within Hokkaido, Japan. The data-set consists of 225 time series of varying length (most from 23 to 31 years long) collected between 1962 and 1992 by the Forestry Agency of the Japanese Government. To see clearly how the periodic behavior changes geographically, we estimate the spectral density functions of the growth rates of all populations using a log-spline method. We subsequently apply functional data analysis to the estimated densities. The functional data analysis is, in this context, analogous to a principal component analysis applied to curves. We plot the results of the analysis on the map of Hokkaido, to reveal a clear transition from relatively stable populations in the southwest and west to populations undergoing 3–4 year cycles in the northeast and east. The degree of seasonality in the vegetation and the rodent demography appear to be strongest in the cyclic area. We briefly speculate that the destabilization of the rodent dynamics is linked to increased seasonalforcing on the trophic interactions in which the gray-sided voles are involved.     

The impact of distance on knowledge transfer effectiveness in multinational corporations

This paper aims to shed light on the interplay of knowledge transfer mechanisms and distance within the MNC. While it is largely undisputed that cross-boarder knowledge flows contribute to the firm's success, our knowledge on the effects of specific transfer mechanisms is scarce. We examine the impact of different dimensions of distance to test the applicability of personal coordination mechanisms (PCM) and technology-based coordination mechanisms (TCM) in situations of differentiation and dispersion. Data on 324 knowledge transfer relationships of MNC units was used to test our hypotheses. While TCM function relatively context-free, we find that PCM are moderated by distance. Our results support moderating effects of geographic, cultural and linguistic distance, which are vital to our understanding of knowledge transfer effectiveness in MNCs.     

Physician-led: good idea or not?

Whether physicians or not, leaders must possess certain skills and qualities to achieve success. Take a look at what's required to be an effective leader.     

Brother correlations in earnings in Denmark, Finland, Norway and Sweden compared to the United States

The correlation in economic status among siblings is a useful “omnibus measure” of the overall impact of family and community factors on adult economic status. In this study we compare brother correlations in long-run (permanent) earnings between the United States, on one hand, and the Nordic countries (Denmark, Finland, Norway and Sweden) on the other. Our base case results, based on very similar sample criteria and definitions for all countries, show that this correlation is above 0.40 in the United States and in the range 0.14–0.26 in the Nordic countries. Even though these results turn out to be somewhat sensitive to some assumptions that have to be made, we conclude that the family and community factors are more important determinants of long-run earnings in the United States than in the Nordic countries. Received: 27 July 2000/Accepted: 7 March 2001 All correspondence to: Anders Bj?rklund. Comments from two referees, conference participants at ESPE2000 and the Canadian Employment Research Forum, seminar participants in Aarhus, Uppsala, Bonn, and Stockholm are gratefully acknowledged. We thank NOS-S for financial support. The Swedish data collection was also supported by HSFR and SFR. The Finnish data were obtained with support from the Yrj? Jahnsson Foundation. We thank Tom Erik Aab? for preparing the Norwegian data, and Esben Agerbo for computational assistance with the Danish data. Responsible editor: John F. Ermisch.     

Sensitivity analyses for the principal ignorability assumption using multiple imputation

In the context of clinical trials, there is interest in the treatment effect for subpopulations of patients defined by intercurrent events, namely disease-related events occurring after treatment initiation that affect either the interpretation or the existence of endpoints. With the principal stratum strategy, the ICH E9(R1) guideline introduces a formal framework in drug development for defining treatment effects in such subpopulations. Statistical estimation of the treatment effect can be performed based on the principal ignorability assumption using multiple imputation approaches. Principal ignorability is a conditional independence assumption that cannot be directly verified; therefore, it is crucial to evaluate the robustness of results to deviations from this assumption. As a sensitivity analysis, we propose a joint model that multiply imputes the principal stratum membership and the outcome variable while allowing different levels of violation of the principal ignorability assumption. We illustrate with a simulation study that the joint imputation model-based approaches are superior to naive subpopulation analyses. Motivated by an oncology clinical trial, we implement the sensitivity analysis on a time-to-event outcome to assess the treatment effect in the subpopulation of patients who discontinued due to adverse events using a synthetic dataset. Finally, we explore the potential usage and provide interpretation of such analyses in clinical settings, as well as possible extension of such models in more general cases.