Change-Point Estimation of Nonstationary I(d) Processes

We examine the least-squares estimator of change point for nonstationary I(d) data with 0.5least-squares estimator, change point, nonstationary I(d) process, spurious change

Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting

Using a sequential conditional independence assumption, this paper discusses fully nonparametric estimation of natural direct and indirect causal effects in causal mediation analysis based on inverse probability weighting. We propose estimators of the average indirect effect of a binary treatment, which operates through intermediate variables (or mediators) on the causal path between the treatment and the outcome, as well as the unmediated direct effect. In a first step, treatment propensity scores given the mediator and observed covariates or given covariates alone are estimated by nonparametric series logit estimation. In a second step, they are used to reweigh observations in order to estimate the effects of interest. We establish root-n consistency and asymptotic normality of this approach as well as a weighted version thereof. The latter allows evaluating effects on specific subgroups like the treated, for which we derive the asymptotic properties under estimated propensity scores. We also provide a simulation study and an application to an information intervention about male circumcisions

An On-Line Personalized Promotion Decision Support System for Electronic Commerce

With the development of the Internet and Electronic Commerce (EC), enterprises have overcome the space and time barriers and are now capable of serving customers electronically. However, it is a great challenge to attract and retain the customers over Internet. One approach is to provide the responsive personalized service to satisfy the customer demand and promote sales at the first time. Hence, in this paper, we propose a decision support system which develops best promotion products based on combinations of different marketing strategies, pricing strategies, and customer behaviors evaluated in terms of multiple criteria. Data mining techniques are utilized to help the business discover patterns to develop on-line sales promotion products for each customer for enhancing customer satisfaction and loyalty. The proposed system consists of four components: (1) establishing marketing strategies, (2) promotion pattern model, (3) personalized promotion products, and (4) on-line transaction model. A simple example is given to illustrate the implementation and application of proposed decision support system

Direct and indirect effects of continuous treatments based on generalized propensity score weighting

This paper proposes semi- and nonparametric methods for disentangling the total causal effect of a continuous treatment on an outcome variable into its natural direct effect and the indirect effect that operates through one or several intermediate variables or mediators. Our approach is based on weighting observations by the inverse of two versions of the generalized propensity score (GPS), namely the conditional density of treatment either given observed covariates or given covariates and the mediator. Our effect estimators are shown to be asymptotically normal when the GPS is estimated by either a parametric or a nonparametric kernel-based method. We also provide a simulation study and an application to the Job Corps program

Estimation of conditional average treatment effects with high-dimensional data

Ministry of Education, Singapore under its Academic Research Funding Tier

Candida lipolytica candidemia as a rare infectious complication of acute pancreatitis: A case report and literature review

Candida lipolytica candidemia is a rare but an emerging pathogenic yeast infection in humans. It can gain access to the bloodstream through intravascular catheterization, especially through central venous catheters in immunocompromised or critically ill patients during hospitalization. In this report, we present a noncatheter-related C. lipolytica candidemia infection in an 84-year-old man who was admitted due to acute pancreatitis. The possible pathogenesis and management of C. lipolytica candidemia are highlighted. It was an unusual infectious complication of acute pancreatitis. Clinicians should be aware that such an opportunistic pathogen can lead to invasive candidemia infection. In clinical practice, systemic antifungal therapy and the removal of the potentially infected central venous catheter might be recommended for the treatment of C. lipolytica candidemia

Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment

While most treatment evaluations focus on binary interventions, a growing literature also considers continuously distributed treatments, e.g. hours spent in a training program to assess its effect on labor market outcomes. In this paper, we propose a Cram\'er-von Mises-type test for testing whether the mean potential outcome given a specific treatment has a weakly monotonic relationship with the treatment dose under a weak unconfoundedness assumption. This appears interesting for testing shape restrictions, e.g. whether increasing the treatment dose always has a non-negative effect, no matter what the baseline level of treatment is. We formally show that the proposed test controls asymptotic size and is consistent against any fixed alternative. These theoretical findings are supported by the method's finite sample behavior in our Monte-Carlo simulations. As an empirical illustration, we apply our test to the Job Corps study and reject a weakly monotonic relationship between the treatment (hours in academic and vocational training) and labor market outcomes like earnings or employment