The Chicago ASA is hosting an annual conference on Weather and Prediction on 3/14. Please come and join us to learn about prediction! Click here to register.
2018 Chicago ASA Annual Conference
Title: Weather and Prediction
Date: March 14, 2018
Location: UIC Student Center East 750 South Halsted Street Chicago, IL 60607
Precision weather forecasting has tangible benefits in our daily lives. The advancement of weather forecasting provides us the confidence to leave our umbrellas at home rather than second guess ourselves about rain. With the advancement of statistical methods such as machine learning techniques, weather and prediction is currently seeing further advancements. In this conference on weather and prediction, we will learn about the forecasting methods to predict future weather, discuss calibration methods to predict future sea levels, illustrate select methods on temperature and precipitation data from various observational networks in the United States, and compare two spatio-temporal random fields that are of interest in climatology. Furthermore, we will also learn how weather affects merchant commodity and energy assets in markets with volatile prices and exchange rates.
- Christopher Wikle: Adapting Science-Based and Machine Learning Methods for Statistical Long-Lead Forecasting of the Ocean, Atmosphere, and Related Processes
- Won Chang: Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
- Sooin Yun: Comparing Two Spatio-Temporal Fields
- Will Kleiber: Statistical Challenges in Creating Historical Weather Products for the United States
- Selvaprabu (Selva) Nadarajah: Commodity and energy operations: Operations, Valuation, and Social costs
8:30 AM - 9:00 AM Registration and Continental Breakfast
9:00 AM - 9:15 AM Introductions led by Kyle Cheek
9:15 AM - 10:30 AM Christopher Wikle (Q&A included)
10:15 AM - 11:30 AM Won Chang (Q&A included)
11:30 AM - 1:00 PM Lunch Break (lunch provided)
1:00 PM - 2:15 PM Sooin Yun (Q&A included)
2:15 PM - 3:30 PM Will Kleiber (Q&A included)
3:30 PM - 3:45 PM Break and Snack
3:45 PM - 5:00 PM Selvaprabu (Selva) Nadarajah (Q&A included)
It’s my pleasure to announce the dates for the 2018 annual meeting of the Association of Clinical and Translational Statisticians (www.actstat.org). Our meeting will be July 28 – 29, 2018 in Vancouver at one of the meeting headquarter hotels. Consistent with prior years, we have planned a full day on the 28th, including a group networking dinner. Our session on the 29th, which will be a half day meeting, will feature our keynote speaker, Dr. Jenny Bryan. She has planned an inspirational session on how to improve our coding in R.
Future announcements will be forthcoming. These will include links to registration pages and a call for abstracts.
We look forward to seeing you in Vancouver this year!
Title: Mixed Models for Intensive Longitudinal Data
Presenter: Donald Hedeker
Date and Time: Wednesday, March 21, 2018, 11:00 a.m. – 1:00 p.m. Central time
Location: Stamler Conference Room
Modern data collection procedures, such as ecological momentary assessments (EMA), experience sampling, and diary methods have been developed to record the momentary events and experiences of subjects in daily life. These procedures yield relatively large numbers of subjects and observations per subject, and data from such designs are often referred to as intensive longitudinal data. Data from such studies are inherently multilevel with, for example, (level-1) observations nested within (level-2) subjects, or observations (level-1) within days (level-2) within subjects (level-3). Thus, mixed models (aka multilevel or hierarchical linear models) are increasingly used for data analysis. In this webinar, focus will be on some of the extended uses of mixed models for analysis of intensive longitudinal data.
A primary focus area of the webinar will be on the modeling of variances from EMA data. In the standard mixed model, the error variance and the variance of the random effects are usually considered to be homogeneous. These variance terms characterize the within-subjects (error variance) and between-subjects (random-effects variance) variation in the data. In EMA studies, up to thirty or forty observations are often obtained for each subject, and there may be interest in characterizing changes in the variances, both within- and between-subjects. Thus, an extension of the standard mixed model will be described which adds a subject-level random effect to the within-subject variance specification. This permits subjects to have influence on the mean, or location, and variability, or scale, of their mood responses. These mixed-effects location scale models have useful applications in many research areas where interest centers on the joint modeling of the mean and variance structure.
Title: Randomization Methods for Multi-center Trials
Presenter: Wenle Zhao, PhD
Date and Time: Friday, March 16, 2018, 12:00 p.m. and 1:00 p.m.
Location: Stamler Conference Room
Dr. Wenle Zhao, Professor of Biostatistics in the Department of Public Health Sciences at the Medical University of South Carolina will be presenting this exciting webinar - Randomization Methods for Multi-center Trials.
In this SCT Webinar, three new randomization designs will be presented as better alternatives to the commonly used permuted block design and the minimization method, with the purpose of enhancing allocation randomness, effectively prevent serious imbalances in large number of baseline covariates, and accurately target any unequal allocations in trials with response adaptive randomization. The block urn design offers the same imbalance control as the permuted block design, but significantly reduces the proportion of deterministic assignments, and therefore reduces the risk of selection bias.
Dr. Zhao is the associate director of the Data Coordination Unit at the Medical University. He has obtained his PhD in biostatistics at MUSC in 1999. His research focus includes subject randomization designs and clinical trial management information system development.