Instructors: Michael Tzen, CCPR UCLA Andy Lin, IDRE UCLA Abstract: In this workshop, attendees will learn how to analyze survey data while accounting for its complex survey design. Using both the R and Stata software packages, we will demonstrate how to specify the survey design, impute any missing data, and analyze the survey outcomes […]
The Center for Social Statistics Presents: Predicting the Evolution of Intrastate Conflict: Evidence from Nigeria The endogenous nature of civil conflict has limited scholars' abilities to draw clear inferences about the drivers of conflict evolution. We argue that three primary features characterize the complexity of intrastate conflict: (1) the interdependent relationships of conflict between actors; […]
Instructor: Ian Lundberg, Ph.D. Student, Sociology and Social Policy, Princeton University Abstract: The Fragile Families Challenge is a scientific mass collaboration that combines predictive modeling, causal inference, and in-depth interviews in order to learn more about the lives of disadvantaged children. Fragile Families Challenge builds on the Fragile Families and Child Wellbeing Study that has […]
The UCLA Departments of Epidemiology, Biostatistics, Statistics and the Center for Social Statistics presents: Causal Methods in Epidemiology: Where has it got us and what can we expect in the future? The principal focus of Dr. Robins’ research has been the development of analytic methods appropriate for drawing causal inferences from complex observational and randomized […]
Instructor: Michael Tzen, CCPR UCLA Abstract: This workshop is a brown bag forum. Participants are encouraged to bring in tangible questions they wish to explore using R. To serve as a background road map, the instructor will provide an abbreviated sample of what he thinks are the most useful features of R. However, the […]
The UCLA Department of Statistics and the Center for Social Statistics presents: Redefine Statistical Significance Daniel Benjamin will discuss his paper (written by him and 71 other authors), “Redefine Statistical Significance”. The paper proposes that the default p-value threshold should be changed from 0.05 to 0.005. The paper is available at this link. Speaker: Daniel […]
The UCLA Department of Statistics and the Center for Social Statistics presents: Redefine Statistical Significance Daniel Benjamin will discuss his paper (written by him and 71 other authors), “Redefine Statistical Significance”. The paper proposes that the default p-value threshold should be changed from 0.05 to 0.005. The paper is available at this link. Speaker: Daniel […]
The UCLA Department of Statistics and the Center for Social Statistics presents: Statistical Significance and Discussion of the Challenges of Avoiding the Abuse of Statistical Methodology Sander Greenland will offer his perspective on the paper, “Redefine Statistical Significance”, which was the topic of the previous week’s seminar. Also he will discuss the challenges of avoiding […]
The UCLA Department of Statistics and the Center for Social Statistics presents: Programming data science with R & the tidyverse Tidy evaluation is a new framework for non-standard evaluation that will be used throughout tidyverse. In this talk, I'll introduce you to the problem that tidy eval solves, illustrated with examples of the various approaches […]
The UCLA Department of Community Health Sciences and the Center for Social Statistics presents: Dynamic Modeling for Health in the Age of Big Data Traditional approaches to public health concerns have conferred great advances in the duration and quality of life. Public health interventions – from improved sanitation efforts, to vaccination campaigns, to contact tracing and […]