Evaluation from a Gender+ Perspective as a Key Element for (Re)gendering the Policymaking Process

ABSTRACT

Feminist scholars have challenged the neutrality of policymaking processes and the outputs resulting from these processes. However, some elements of policymaking have not been studied as well as others. In this article I explore the concept of evaluation from a gender+ perspective as an essential step for a complete gender mainstreaming strategy, which can help to identify gender issues that should be integrated into the content of evaluated policies and to ensure gender does not get lost in the policymaking process. This exploration is carried out by relying on feminist policy and evaluation studies.     

Monitoring the parameter vector of regression models with time-to-event response in phase II processes

In most of the existing specialized literature, monitoring regression models are a special case of profile monitoring. However, not every regression model always represents appropriately a profile data structure. This is clearly the case of the Weibull regression model (WRM) with common shape parameter γ. Even though it might be thought that existing methodologies (especially likelihood-ratio (LRT)-based methods) for monitoring generalized linear profiles can also be successfully applied to monitoring regression models with time-to-event response, it will be shown in this paper that those methodologies work fairly acceptable just for data structures with 1000 observations at least approximately. It was found out that some corrections, often referred to as Bartlett's adjustments, are needed to be implemented in order to improve the accuracy of using the asymptotic distributional properties of the LRT statistic for carrying out the monitoring of WRM with relatively small and moderate dimensions of the available datasets. Simulation studies suggest that the use of the aforementioned corrections make the resulting charts work quite acceptable when available data structures contain 30 observations at least. Detection abilities of the proposed schemes improve as dataset dimension increases.     

Estimation of variance in bivariate normal distribution after the preliminary test of homogeneity

A preliminary test estimator of variance in the bivariate normal distribution is proposed after the Pitman–Morgan test of homogeneity of two variances. The bias and mean square error of the estimator are derived. The relative efficiency (RE) of the preliminary test estimator is studied. Computations and 3D graphs of RE for different parameters are analyzed. In order to get the maximum RE, recommendations of the significance level for the preliminary test are given for various sample sizes by using the max–min criterion.     

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论行政相对人知情权的司法救济

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关注公民公平感——我国部分公民公平感调查报告

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