The US President's Emergency Plan for AIDS Relief

This article analyses the US response under former President George W. Bush to the global HIV/AIDS epidemic at the intersection of neo-conservatism and neo-liberalism, highlighting the various ways their distinct gender logics collide to reproduce masculine privilege and gender inequalities on a global scale. The President's Emergency Plan for AIDS Relief (PEPFAR) is the United States global HIV/AIDS policy and is the largest commitment made by any single nation for an international health project. My analysis is based on PEPFAR's ‘formal’ policy texts, including its authorizing legislation, five-year strategic framework and specific policy directives for recipient organizations. In addition, I examine more ‘informal’ texts like Congressional reports and Presidential speeches delivered by George W. Bush on various occasions. Drawing on a rich body of feminist ethnographic work in the fields of global governance, international political economy, organizational theory and sexuality and masculinity studies, the following article examines the various ways market-based norms and practices can legitimate the moral imperatives of neo-conservatism to promote ‘traditional’ values and institutions in the global South as leading solutions to global problems and insecurities.     

Tolerance Limits Based on the Multivariate MaxMin Chart

In a previous paper, we have showed how to obtain sequences of number proved random. With this aim, we used sequences of noises y_n such that the conditional probabilities have Lipschitz coefficients not too large. We transformed them using Fibonacci congruences. Then, we obtained sequences x_n which admit the IID model for correct model. This method consisted to value the work of Marsaglia in order to build his CD-ROM. But we did not use Rap Music (as Marsaglia), but texts files. This method also uses an extractor and at the same time the notion of correct models. In this paper, we apply this method to numbers provided by machines or chips. Unfortunately, it is less sure than they have Lipschtiz coefficient not too large. But we can solve this problem: it suffices to use the Central Limit Theorem. We do it modulo 1. In this case, we use a new limit theorem, the XOR Limit theorem : asymptotic distribution of sum of random vectors modulo 1 are asymptotically independent. Then Lipschtiz coefficient of associated sequences are not too large and we can obtain IID sequences by using Fibonacci congruences.     

Estimation of Semiparametric Models when the Criterion Function Is Not Smooth

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some nonparametric estimators that can themselves depend on the parameters to be estimated. Our results extend existing theories such as those of Pakes and Pollard (1989), Andrews (1994a), and Newey (1994). We also show that bootstrap provides asymptotically correct confidence regions for the finite dimensional parameters. We apply our results to two examples: a ‘hit rate’ and a partially linear median regression with some endogenous regressors.     

The Role of Government in Macro-Level Quality Development: A Case Study of South Korea

Public Organization Review - This study investigates the South Korean government’s effort to promote macro-level quality development. Using the single case study method, the authors examined...     

Natural cubic splines for the analysis of Alzheimer's clinical trials

Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.     

A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient

The Journal of Economic Inequality - We propose an extension of the univariate Lorenz curve and of the Gini coefficient to the multivariate case, i.e., to simultaneously measure inequality in more...