### Stata Course

All course materials for the "Statistical Modelling in Stata" course can be found here. I'm currently updating the slides and handouts for 2023: I've kept a copy of the old material here, but I will delete this once the new course is completed.

### Guide to Propensity Analysis

A guide to performing propensity analyses in Stata can be found here. It covers how to calculate propensity scores, check that they work, and use them to estimate the effect of an exposure. The do-file used to perform all of the analyses is available as an appendix in the guide, or you can download it here if that is more convenient.

### Guide to Multiple Imputation

A guide to multiple imputation, and the dataset used for the examples in the guide can he found here. This is of particular interest if you need to impute continuous variables with a non-normal distribution.

### Tutorial in competing risks

This practical aims to illustrate some of the problems caused by competing risks in Survival Analysis, and present some of the solutions available in Stata. It is based on "Tutorial in biostatistics: Competing risks and multi-state models" by Putter H, Fiocco M, and Geskus RB, published in Statistics in Medicine 2007 volume 26, pages 2389--2430. The original tutorial used R for the analysis, this uses stata instead. A do-file to perform the entire analysis can be found here.

### Guide to using the Linux Workstation

Some notes about connecting to the Linux workstation from a PC. Only of interest to people within the ARC epidemiology unit, who could be given access to it.

### Stata Software

I have written some software for Stata. To view it, start stata and type
``` net from http://personalpages.manchester.ac.uk/staff/mark.lunt ```
in the command window.
Alternatively, all the files are available here. However, the help files are written in stata's own SMCL language, so are not easy to read other than in stata. The ado files should be fairly comprehensible to someone with a good knowledge of the C programming language and some familiarity with statistical concepts, although some knowledge of the peculiarities of stata's own programming language would be very helpful.