Causal Inference Using Stata: Estimating Average Treatment Effects
Learn how and when to use Stata’s treatment-effects estimators to analyze treatment effects in observational data. Use regression adjustment, inverse probability weights, doubly robust methods, propensity-score matching, and covariate matching to estimate average treatment effects (ATEs) and ATEs on the treated. We will cover the conceptual and theoretical underpinnings of treatment effects as well as many examples using Stata.
A Crash Course in Mixture Design of Experiments
Advance your R&D experimentation skills via this essential webinar on mixture experiments. A compelling demo lays out what makes mixture design of experiments (DOE) so effective for accelerating your formulation efforts. Discover how to:
• Identify key characteristics leading to a mixture experiment
• Use mixture DOE to create optimal formulations
• Map out your sweet spot with graphical tools
The fuel provided in this 1-hour webinar will kick-start your first formulation designed experiment.
Deploying DOE to Predict Process Performance
Design of experiments (DOE) is a tried-and-true, multifactor quality tool for identifying key process drivers. This webinar demonstrates how to deploy DOE to create reliable prediction models. Similar in concept to estimating the power of a design, prediction precision becomes the key evaluation statistic. A case study demonstrates how to confirm that a particular design will provide the desired results - more reliable process settings.
NetCourse: Introduction to Stata
Learn how to use all of Stata's tools and become a sophisticated Stata user. You will understand the Stata environment, how to import and export data from different formats, how Stata's intuitive syntax works, data management in Stata, matching and merging, how to analyze subgroups of data, how to reproduce your work and document it for publication and review, how to interact with the Stata community online, and more.
NetCourse: Introduction to Stata Programming
Become an expert in organizing your work in Stata. Make the most of Stata's scripting language to improve your workflow and create concretely reproducible analyses. Learn how branching, looping, flow of control, and accessing stored estimation results can speed up your work and lead to more complete analyses. Learn about bootstrapping and Monte Carlo simulations, too.
NetCourse: Statistical Graphics Using Stata
Learn how to communicate your data with Stata's powerful graphics features. This course will introduce different kinds of graphs and demonstrate how to use them for exploratory data analysis. Topics include how to use graphs to check model assumptions; how to format, save, and export your graphs for publication using the Graph Editor.
Using Stata Effectively: Data Management, Analysis, and Graphics Fundamentals
Become intimately familiar with three components of Stata: data management, analysis, and graphics. This course is aimed at both new Stata users and those who wish to learn techniques for efficient day-to-day use of Stata.
NetCourse: Introduction to Panel Data Using Stata
Become an expert in the analysis and implementation of linear, nonlinear, and dynamic panel-data estimators using Stata. This course focuses on the interpretation of panel-data estimates and the assumptions underlying the models that give rise to them. The course is geared for researchers and practitioners in all fields.
NetCourse: Univariate Time Series with Stata
Learn about univariate time-series analysis with an emphasis on the practical aspects most needed by practitioners and applied researchers. We provide lesson material, detailed answers to the questions posted at the end of each lesson, and access to a discussion board on which you can post questions for other students and the course leader to answer.
NetCourse: Introduction to Survival Analysis Using Stata
Learn how to effectively analyze survival data using Stata. We cover censoring, truncation, hazard rates, and survival functions. Topics include data preparation, descriptive statistics, life tables, Kaplan–Meier curves, and semiparametric (Cox) regression and parametric regression.
Event Conditions
Course registration is binding. Upon cancellation more than 8 working days before the course start date, we invoice 50% of the course fee. Upon cancellation less than 8 working days before the course start date, we invoice the full course fee. Click here to read the full Terms and Conditions!