Multilevel Exponential-Family Random Graph Models (mlergm)Estimates exponential-family random graph models for multilevel network data, assuming the multilevel structure is observed. The scope, at present, cov …

Exercise template for computing the 2-sided confidence interval (with extended Moodle processing) for the mean based on a random sample.

We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive code parts or by creating overviews of our projects. At first, there was no plan to make a package, but soon I realised, that it will be much easier to share and improve those functions, if they are within a package. Up till the 24th December I will present one function each day from helfRlein. So, on the 8th day of Christmas my true love gave to me…

Marketing analytics is a diverse field, with both academic researchers and practitioners coming from a range of backgrounds including marketing, operations research, statistics, and computer science. This paper provides an integrative review at the boundary of these three areas. The topics of visualization, segmentation, and class prediction are featured. Links between the disciplines are emphasized. For each of these topics, a historical overview is given, starting with initial work in the 1960s and carrying through to the present day. Recent innovations for modern large and complex ‘big data’ sets are described. Practical implementation advice is given, along with a directory of open source R routines for implementing marketing analytics techniques. Marketing Analytics: Methods, Practice, Implementation, and Links to Other Fields

Time really does fly. It’s been 5 months since Delhi NCR useR group had come into being and our first meetup. It was a successful event which included sessions featuring an R-core member and a veteran data scientist. More importantly, the 50+ community members who’d turned up took part in stimulating discussions and got to know about each other’s work. You can find videos from the session here.

Many of our projects involve getting doctors, nurses, and medical students to collect data on the patients they are looking after. We want to involve many of them in data analysis, without the requirement for coding experience or access to statistical software. To achieve this we have built Shinyfit, a shiny app for linear, logistic, and Cox PH regression.

I’m just gonna put this xkcd comic right here.

By Sam Finlayson, MD-PhD Student at Harvard-MIT.Original. Reposted with permission.The following is a snapshot of the original that will be updated over time

Predicting future stock market structure by combining social and financial network information