On Old-Fashioned Versus Modern Homonegativity Distinction: Evidence From Poland

Psychological research on prejudice against homosexuals distinguishes between old-fashioned (traditional) and modern (contemporary) homonegativity, which differ with regard to their content, correlates, and consequences. The current research offers evidence for the validity of old-fashioned versus modern homonegativity distinction in the post-communist, East European context. In Studies 1 and 2 (Ns = 295 and 327, respectively) the Polish adaptations of the non-gendered and gendered Homonegativity Scale (Morrison, Parriag, & Morrison, 1999) and the Modern Homonegativity Scale (Morrison & Morrison, 2003) were developed. Furthermore, divergent (discriminant) validity of traditional and contemporary anti-homosexual prejudice was demonstrated. Old-fashioned and modern homonegativity exhibited differential relationships with social distance and support for same-sex couples’ relational rights.     

Residential mobility and the spatial dispersion of personal networks: Effects on social support

Using a representative national sample of personal networks, this article explores how the spatial dispersion of networks, residential mobility and social support are linked. Three issues will be addressed here. Firstly, how is the spatial dispersion of personal networks related to individuals’ social characteristics, network composition and residential mobility? Secondly, how do the spatial dispersion of networks, residential mobility and their combined effect influence the number and (thirdly) the structure of emotional support ties? Results showed that the extent of the support was affected neither by the geographical distribution of the networks nor by residential mobility. Living far from one's birthplace, however, exerted two distinct, and opposite effects on the support network structure. On the one hand, mobility led to high spatial dispersion of personal contacts, which in turn favored a sparsely knit network centered around the mobile individual. On the other hand, by controlling for the effect of distance between the contacts, we found that individuals that cited long-distance ties tended to be part of more transitive support networks than those that cited local ties. We interpreted the latter effect as evidence that transitive ties may survive greater spatial distances than intransitive ones. These findings are discussed in view of spatial mobility and social network research.     

Estimation of parameters of inverse Weibull distribution and application to multi-component stress-strength model

The problem of estimation of the parameters of two-parameter inverse Weibull distributions has been considered. We establish existence and uniqueness of the maximum likelihood estimators of the scale and shape parameters. We derive Bayes estimators of the parameters under the entropy loss function. Hierarchical Bayes estimator, equivariant estimator and a class of minimax estimators are derived when shape parameter is known. Ordered Bayes estimators using information about second population are also derived. We investigate the reliability of multi-component stress-strength model using classical and Bayesian approaches. Risk comparison of the classical and Bayes estimators is done using Monte Carlo simulations. Applications of the proposed estimators are shown using real data sets.     

An efficient and fast algorithm for estimating the frequencies of superimposed exponential signals in zero-mean multiplicative and additive noise

In this paper, we consider the superimposed exponential signals in zero-mean multiplicative and additive noise when all the noise are independently and identically distributed. We use a three-step iterative procedure to estimate the frequencies of the considered model. It is observed that the estimators are consistent and work quite well in terms of biases and mean square errors. Moreover, the convergence rate of the estimators attains O _p (N ^?3/2), which is the best convergence rate in the case of only additive noise and constant amplitude.     

Optimal split‐plot orthogonal arrays

It is well known that many industrial experiments have split‐plot structures. Compared to completely randomised experiments, split‐plot designs are more economical and thus have received much attention among researchers. Much work has been done for two‐level split‐plot designs. In this article, we consider split‐plot designs with factors of three, more than three, or mixed levels and with both qualitative and quantitative factors. We show that if two designs with both qualitative and quantitative factors are geometrically isomorphic, then their generalised wordlength patterns are identical. Three design scenarios are considered for optimal designs. The corresponding wordlength patterns are defined and the minimum aberration mixed‐level split‐plot designs having 18 and 36 runs are tabulated.     

Geometric Anisotropic Spatial Point Pattern Analysis and Cox Processes

We consider spatial point processes with a pair correlation function, which depends only on the lag vector between a pair of points. Our interest is in statistical models with a special kind of ‘structured’ anisotropy: the pair correlation function is geometric anisotropic if it is elliptical but not spherical. In particular, we study Cox process models with an elliptical pair correlation function, including shot noise Cox processes and log Gaussian Cox processes, and we develop estimation procedures using summary statistics and Bayesian methods. Our methodology is illustrated on real and synthetic datasets of spatial point patterns.     

Influence measure for the L1 regression

Because outliers and leverage observations unduly affect the least squares regression, the identification of influential observations is considered an important and integrai part of the analysis. However, very few techniques have been developed for the residual analysis and diagnostics for the minimum sum of absolute errors, L₁ regression. Although the L₁ regression is more resistant to the outliers than the least squares regression, it appears that outliers (leverage) in the predictor variables may affect it. In this paper, our objective is to develop an influence measure for the L₁ regression based on the likelihood displacement function. We illustrate the proposed influence measure with examples.     

Buffon's needle and the estimation of migration distances

A procedure is suggested for estimating migration distances from data on the proportion of migrants crossing regional boundaries. The method makes use of Buffon's needle, a problem in geometrical probability from the eighteenth century that was originally used as an empirical means of estimating π. The procedure is described for various scenarios that differ in their assumptions about region shape, the spatial distribution of population, and the distribution of migration distances. An application to migration distances in the United States is given, and additional attention is given to the estimation of intraregional migration distances.     

A more general methodology for fitting global cross-ratio models for discrete longitudinal responses

In this paper, we focus on repeated measurement problems, comprising an interesting research area in statistics. We study longitudinal data which arise when outcomes are observed repeatedly on each experimental subject at several points. We focus on a marginal approach for this type of data with lack of independence among the observations proposed by Dale [Global cross-ratio models for bivariate, discrete, ordered responses. Biometrics. 1986;42(4):909–917] for bivariate, discrete, ordered responses. We propose an alternative estimation based on divergence measures to the full likelihood method proposed in that paper. Finally, a wide simulation study and a data example that illustrates the new methodology is provided.