R: Regression Analysis in R

This course is for new users who have learnt how to get data into R already, and know how to operate basic syntax. Emphasis will be on examples of running applied analyses of regression models for continuous, binary and ordinal outcomes using standard R procedures. Half a dozen libraries will be introduced that enables importing of data and running of linear, binary, ordinal and nominal outcome regression models in R.

• Working knowledge of R
• Familiarity with simple statistical concepts

Number of sessions: 2

• Linear regression for continuous outcomes
• Bootstrapping standard errors
• Logistic regression
• Logistic regression for clustered data
• Ordinal regression for multi-category outcomes that can be ordered
• Logit and probit models
• Nominal regression (in brief) for unordered multicategory outcomes
• Categorical covariates using xi:

Presentations, demonstrations and practicals.

R v. 2.9.1 on PWF Windows

Two half day sessions

• Scientific Computing
• Statistical and Mathematical Software