The last three years have seen explosive growth in the variety and sophistication of interactive online graphics. These are mostly implemented in the web language JavaScript, with the Data Driven Documents (D3) library being the most popular and flexible at present. Leaflet is a mapping library...

Residual confounding is a major problem in analysis of observational data, occurring when a confounding variable is measured coarsely (censored, heaped, missing, etc.) and hence cannot be fully adjusted to obtain a causal estimate by usual means such as multiple regression. The analysis of...

Much interest has been focused on animated graphical displays of data in recent years, although this mostly involves some expertise with specialized software and programming. There is a lack of simple tools for data analysts to use to produce animations. In this presentation, I will show how...

The last three years have seen explosive growth in the variety and sophistication of interactive online graphics. These are mostly implemented in the web language JavaScript, with the D3 (Data Driven Documents) library being the most popular and flexible at present. Leaflet is a mapping library...

Tundra and taiga ecosystems comprise nearly 40 % of the terrestrial landscapes of Canada. These permafrost ecosystems have supported humans for more than 4500 years, and are currently home to ca. 115,000 people, the majority of whom are First Nations, Inuit and Métis. The responses of these...

The problem of relating genotype (as represented by amino acid sequence) to phenotypes is distinguished from standard regression problems by the nature of sequence data. Here we investigate an instance of such a problem where the phenotype of interest is HIV-1 replication capacity and contiguous...

This note is the authors' response to the Reader's Reaction provided by Foulkes and De Gruttola as published in Statistical Applications in Genetics and Molecular Biology

We identify operating exposure as the most important and difficult to manage component of exchange risk. Our model identifies three components of foreign exchange exposure: direct operating exposure, the market demand effect, and the competitive effect. The size and relative importance of these...

Background: Random effects are commonly modeled in multilevel, longitudinal, and latent-variable settings. Rather than estimating fixed effects for specific clusters of data, "predictions" can be made as the mode or mean of posterior distributions that arise as the product of the random effect...