Matching methods for causal inference selectively prune observations from the data in order to reduce model dependence. They are successful when simultaneously maximizing balance (between the treated and control groups on the pre-treatment covariates) and the number of observations remaining in the data set. However, existing matching methods either fix the matched sample size ex ante and attem...

Empirical measurement of interventions to address significant global health and development problems is necessary to ensure that resources are applied appropriately. Such intervention programs are often deployed at the group or community level. The gold standard design to measure the effectiveness of community-level interventions is the community-randomized trial, but the conditions of these tr...

March 19, 2015 Version 2.0-10 Date 2015-03-18 Author Diego Colombo, Alain Hauser, Markus Kalisch, Martin Maechler Maintainer Markus Kalisch Title Methods for Graphical Models and Causal Inference Description Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational ...

A rcccnt trend in cxpcrt systems rcscarch has been toward systems which reason from descriptions of causnl processes in the domain, rather than from the surface cffccts. ‘I’his is the “causal model” versus “cinpirical association” distinction prcscntcd in [2]. Typically, this involves creating a dctailcd model of the physical proccsscs which undcrly the domain. ‘I’his model must support infcrcn...

Telemedicine, enabled by state-of-art information technology, is rapidly gaining awareness in many countries. Despite the advanced telecommunication infrastructure, the introduction of telemedicine in Hong Kong has been slow. Hong Kong’s monopolistic health care system provides an answer for the protracted development of telemedicine in the region. This study attempts to reach a theoretical und...

Predicting patient outcome is an important task in medical decision making, as clinician expectations of outcome drive testing and treatment decisions. Accurate models can assist clinicians by capitalizing on information from a broad spectrum of features to predict outcome. In an article in this journal, ‘A study in transfer learning: leveraging data from multiple hospitals to enhance hospital-...

Commercially successful video games easily sell more than one million units in the US market alone and gross more than $ 100 million. Few research approaches have asked the question what makes a video game succeed in the market. This paper focuses on the role of external information sources. As video games are experience goods whose value for the consumer only becomes apparent after he or she h...

The advance of high-throughput next-generation sequencing technology makes possible the analysis of rare variants. However, the investigation of rare variants in unrelated-individuals data sets faces the challenge of low power, and most methods circumvent the difficulty by using various collapsing procedures based on genes, pathways, or gene clusters. We suggest a new way to identify causal rar...