Title: Shiny 101: From Nothing to Deployed
Presenter: Sean Lopp, RStudio
Date and Time: Tuesday, June 20, 2017, 1:00 p.m. – 2:30 p.m. Eastern time
Sponsor: Section on Statistical Consulting
Registration Deadline: Friday, June 16, at 12:00 p.m. Eastern time
Shiny is a popular R package for creating interactive web applications from within R. This webinar will introduce the Shiny package and provide an overview of Shiny's use cases. We'll discuss reactivity, user interfaces, and different options for deploying shiny applications. We'll also build and deploy a simple shiny application from scratch.
About the Presenter:
Sean has a degree in mathematics and statistics and worked as an analyst at the National Renewable Energy Lab before making the switch to customer success at RStudio. Sean has worked on statistical modeling projects ranging from autonomous vehicles to infant sleep dynamics. At RStudio, Sean works with customers to increase the value they receive from Shiny, R Markdown, and the IDE.
Member of the Section on Statistical Consulting: $40
ASA Member: $65
Each registration is allowed one web connection and one audio connection. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).
Registration is now closed.
Registered persons will be sent an email the afternoon of Friday, June 16, with the access information to join the webinar and the link to download and print a copy of the presentation slides.
Title: Network Analysis in Cross-sectional Data Using R
Presenter: Eiko Fried
Date and Time: Thursday, October 19, 2017, 12:00 p.m. – 2:00 p.m. Eastern time
Sponsor: Mental Health Statistics Section
Registration Deadline: Tuesday, October 17, at 12:00 p.m. Eastern time
Analysis of mental health data is usually based on sum-scores of symptoms or the estimation of factor models. Both types of analyses disregard direct associations among symptoms that are well-understood in clinical practice: mental disorders can be conceptualized as vicious circles of problems that are hard to escape. A novel research framework, the network perspective on psychopathology, understands mental disorders as complex networks of interacting symptoms. Despite its comparably recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in recent years.
In this webinar, we will use R to learn about (1) network estimation, (2) network inference, and (3) network stability in cross-sectional data. Regarding network estimation, the state-of-the-art network model for cross-sectional data is the pairwise Markov Random Field or regularized partial correlation network that estimates the conditional dependence relations among items. We will learn to estimate appropriate network models for our data: the Ising Model for binary data, and the Gaussian Graphical Model for metric data. In this first section, we will also cover regularization methods that avoid the estimation of false positive associations in networks. The second topic, network inference, covers graph theoretical measures such as centrality that allow us to interpret networks. What symptoms are most connected with other symptoms? Finally, network stability allows us to gain insight into the robustness of our networks. We conclude the webinar with advanced methods such as the statistical comparison of networks, and how to deal with ordinal and mixed data. Is it noteworthy that network analysis is not limited to psychopathology data, but has been employed to study other psychological constructs such as intelligence, personality traits, and attitudes.
Member of the Mental Health Statistics Section: $60
ASA Member: $90
Each registration is allowed one web connection. Sound is received via audio streaming from your computer’s speakers. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).
Registered persons will be sent an email the afternoon of Tuesday, October 17, with the access information to join the webinar and the link to download and print a copy of the presentation slides.