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In many practical applications, a multivariate outcome is measured on two or more groups of subjects. When these variables are analyzed separately, the information is not fully exhausted, as possible dependencies among the endpoints are not considered. Within parametric frameworks, a number of literature exists to test such multivariate outcomes. Also, a few methods have been proposed using a fully non parametric approach. It is of particular interest to test the hypothesis of no treatment effect against conjectured patterns that are associated with treatment efficacy. We proposed a rank-based test for detecting pre-specified alternative patterns across all endpoints. The test statistic we have derived is a multivariate generalization of a recent non parametric univariate test for alternative patterns. Since we do not require the continuity of the distribution functions, the newly proposed test is applied to data with ties, in particular, to multivariate-ordered categorical data. Moreover, the test is invariant under monotone transformations of the responses and the weights describing the alternative pattern. Finite sample performance of the proposed test is assessed through a simulation study and comparisons are made with the most popular test for one-sided multivariate problems. The application of the test statistic is demonstrated with an electroencephalogram dataset. [ABSTRACT FROM AUTHOR]

The World Health Organization stipulated that intimate partner violence is one of the most common forms of violence against women and includes physical, sexual, and emotional abuse and controlling behaviors by an intimate partner. Opposition of women against any form of violence at home, beating by their husbands in particular, is a manifestation of readiness to assert their personal rights. This study used data from the 2011 Ethiopian Demographic and Health Survey to identify some predictors to determine attitudes of married Ethiopian women toward wife beating. The dataset used consisted of 5,818 married women of the reproductive age group 15 to 49 years. While 1,393 (24%) married women did not oppose wife beating, a total of 4,425 (76%) opposed the practice. In the binary multiple logistic regression analysis, age, economic status, level of education, employment status of a woman, number of children living in the household, region (federal administrative regions delineated on the basis of ethnicity), place of residence (urban vs. rural), religion, and husband's level of education have been included as possible socioeconomic and demographic determinants of women's attitudes toward wife beating. The findings showed that the predictors region, place of residence, number of living children in a household, and religion were significantly associated with women attitudes toward wife beating. [ABSTRACT FROM AUTHOR]

Abstract The choice of initial weighting matrix and the problem of instruments proliferation are crucial issues in generalized method of moments (GMM) estimators of dynamic panel models. In this study, we propose alternative system GMM estimators that utilize suboptimal initial weighting matrices together with reduced instruments set (specifically lag-limited and partially collapsed instruments). Comparison of the performance of the proposed estimators against the conventional estimator was undertaken in terms of bias, root mean squared error (RMSE) and coverage probabilities through Monte Carlo simulations. Our simulation results revealed that sub-optimally weighted system GMM estimator adopting partially collapsed instruments outperforms the standard GMM estimator in terms of both bias and RMSE for large T and large variance ratios as the coefficient of the lagged dependent variable gets close to zero. Under these scenarios, the system GMM estimators based on reduced instruments were also found to perform well in terms of coverage probabilities. As the process approaches a random walk, however, there is no considerable gain from the use of suboptimal initial weights matrix and reduced instruments in general. [ABSTRACT FROM AUTHOR]