Introduction to Bayesian Statistics in Stata
April 12, 2021 | 11:30am-1 pm
Bayesian Multilevel/Longitudinal Modeling
May 10, 2021 | 11am-1pm
Item Response Theory (IRT) and Bayesian IRT
June 14, 2021 | 11am-1pm
Participants are welcome to use their own SPSS program (version v26 or v27). For those who do not have SPSS, please use the free program from UCI OIT Virtual Computer Lab. UCI OIT offers free access to SPSS when you log into the Virtual Computer Lab using your UCINetID:
The cost of the workshop is $15.
Free for registered participants to attend
|8:30 – 9:30am||Basic Stata Commands|
|9:30 – 10:30am||Basic Stata Estimation Commands|
|10:45 – 11:45am||Intro to Psychometrics with Stata: Topics include reliability, Cohen’s kappa statistic, canonical correlation, Cronbach’s alpha, exploratory factor and confirmatory factor analysis, factor rotations, multivariate analysis of variance (MANOVA), contrasts and pairwise comparisons, structural equation modeling (SEM), item response theory (IRT), and latent class analysis (LCA).|
|1 – 2:15pm||Intro to Causal Inference and Treatment Effects Basic concepts of causal inference including counterfactuals and potential outcomes are introduced. Demonstration of Stata’s -teffects- suite of commands to fit causal models using propensity score matching, inverse-probability weighting, regression adjustment, “doubly-robust” estimators that use a combination of inverse-probability weighting with regression adjustment, and nearest-neighbor matching.|
|2:30 – 4pm||Causal Inference for Complex Observational Data Concepts in missing data such as missing at random (MAR), missing not at random (MNAR), and unobserved confounding are introduced. This talk will demonstrate how to use standard maximum likelihood estimation to fit extended regression models (ERMs) that deal with all of these common issues alone or simultaneously.|
Tidyverse is a set of R packages that are known for their consistent grammar. This workshop will introduce packages in the Tidyverse collection and other packages that use tidy principles. It will cover summarizing data with descriptive statistics and visualizations, wrangling data, statistical modeling and writing reproducible reports with R Markdown. Prerequisite Knowledge: Some experience with working with data in R, Excel, SAS, SPSS, Python or any other tool.
Mine Dogucu is Assistant Professor of Teaching in the Department of Statistics. Her work focuses on integrating data science and computing in the statistics curriculum, making Bayesian education accessible at the undergraduate level, and instructor training. She has been an R user for more than 10 years and has been using Tidyverse in the last 3 years.
University of California, Irvine
School of Information & Computer Science
Department of Statistics
Second Floor, Room 2011
Breakfast and lunch will be provided.
Please bring a laptop to the workshop.
Register Online: https://tinyurl.com/RTheTidyWay
Professor and Chair
UCI’s Department of Statistics
This short course will cover the fundamentals of clinical trials design including both primary design issues as well as proper conduct and implementations. After this course researchers will be familiar with specific design issues including screening studies, planning statistical tasks and the essential elements of a clinical protocol. The important aspects of proper implementation including randomization, blinding, and surrogate endpoints will be discussed. The course will not require heavy statistical abilities but will instead focus on the essential elements of design to best ensure valid, generalizable, and reproducible trial results. This course is great if you are new to trial design or just want a refresher on the fundamentals.
UCI’s Donald Bren Hall – Conference Room 2011
Course materials and lunch will be provided.
Power analysis is the process of determining sample size for a research study. Performing power analysis at the planning stage is crucial to any research investigation. This two-day hands-on course introduces the key conceptual elements and practical tools for performing power analysis and covers power analysis for tests on means, one-way ANOVA, proportions, correlation and multiple regression.
Who should attend: Researchers from all fields who are interested in learning what power analysis is and how it could be useful in their research.
Multipurpose Science & Technology Building (MSTB)
415 East Peltason Drive, Room 226
Irvine, CA 92617