Statistica Neerlandica 

About: Statistica Neerlandica is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Estimator & Asymptotic distribution. It has an ISSN identifier of 0039-0402. Over the lifetime, 1506 publications have been published receiving 24382 citations.

Robustness issues in multilevel regression analysis

Abstract: A multilevel problem concerns a population with a hierarchical structure. A sample from such a population can be described as a multistage sample. First, a sample of higher level units is drawn (e.g. schools or organizations), and next a sample of the sub-units from the available units (e.g. pupils in schools or employees in organizations). In such samples, the individual observations are in general not completely independent. Multilevel analysis software accounts for this dependence and in recent years these programs have been widely accepted. Two problems that occur in the practice of multilevel modeling will be discussed. The first problem is the choice of the sample sizes at the different levels. What are sufficient sample sizes for accurate estimation? The second problem is the normality assumption of the level-2 error distribution. When one wants to conduct tests of significance, the errors need to be normally distributed. What happens when this is not the case? In this paper, simulation studies are used to answer both questions. With respect to the first question, the results show that a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second-level standard errors. The answer to the second question is that only the standard errors for the random effects at the second level are highly inaccurate if the distributional assumptions concerning the level-2 errors are not fulfilled. Robust standard errors turn out to be more reliable than the asymptotic standard errors based on maximum likelihood.

Non-and semi-parametric estimation of interaction in inhomogeneous point patterns

Abstract: We develop methods for analysing the ‘interaction’ or dependence between points in a spatial point pattern, when the pattern is spatially inhomogeneous. Completely non-parametric study of interactions is possible using an analogue of the K-function. Alternatively one may assume a semi-parametric model in which a (parametrically specified) homogeneous Markov point process is subjected to (non-parametric) inhomogeneous independent thinning. The effectiveness of these approaches is tested on datasets representing the positions of trees in forests.

Panel unit root tests under cross-sectional dependence

Abstract: In this paper alternative approaches for testing the unit root hypothesis in panel data are considered. First, a robust version of the Dickey-Fuller t-statistic under contemporaneous correlated errors is suggested. Second, the GLS t-statistic is considered, which is based on the t-statistic of the transformed model. The asymptotic power of both tests is compared against a sequence of local alternatives. To adjust for short-run serial correlation of the errors, we propose a pre-whitening procedure that yields a test statistic with a standard normal limiting distribution as N and T tends to infinity. The test procedure is further generalized to accommodate individual specific intercepts or linear time trends. From our Monte Carlo simulations it turns out that the robust OLS t-statistic performs well with respect to size and power, whereas the GLS t-statistic may suffer from severe size distortions in small and moderate sample sizes. The tests are applied to test for a unit root in real exchange rates.

Modelling association football scores

Abstract: Previous authors have rejected the Poisson model for association football scores in favour of the Negative Binomial. This paper, however, investigates the Poisson model further. Parameters representing the teams' inherent attacking and defensive strengths are incorporated and the most appropriate model is found from a hierarchy of models. Observed and expected frequencies of scores are compared and goodness-of-fit tests show that although there are some small systematic differences, an independent Poisson model gives a reasonably accurate description of football scores. Improvements can be achieved by the use of a bivariate Poisson model with a correlation between scores of 0.2.

The concept of Ro in epidemic theory

Abstract: In epidemiology R0 denotes the average number of secondary cases of an infectious disease that one case would generate in a completely susceptible population. This concept is among the foremost and most valuable ideas that mathematical thinking has brought to epidemic theory. In this contribution, we first review the historical development of Ro, from demography to epidemiology, proceed to give an exposition of the recently formalised theory to define and calculate R0 for structured populations, return to the interaction of demography and epidemiology for an example of the use of the concept to study vaccination campaigns and finally we deal with statistical aspects of estimating R0. In the appendix we discuss some issues of current attention.