Medical Statistics with Stata
Postgraduate course
- ECTS credits
- 2
- Teaching semesters
- Autumn, Spring
- Course code
- MEDSTATA
- Number of semesters
- 1
- Teaching language
- Norwegian.English if International PhD candidates.
- Resources
- Schedule
- Reading list
Course description
Objectives and Content
Aim:
The course will give an introduction to the statistics program STATA and the most basic statistical methods used in medical and epidemiologic research
Content:
- Data management, including generating new variables, merging files and switching between wide and long format
- Loops and various data management commands in Stata for streamlining work in Stata
- Stata command syntax
- Commands for making automatic tables with results from statistical analyses
- Use of do-files to make the analyses more efficient and document you work and to make reproducible results
- Use help-files, Stata documentation and online resources
- Use log-files as documentation of analysis results
- Descriptive statistics
- Analysis of continuous variables (t-test, correlation, linear regression)
- Analysis of categorical variables (chi-square test, Fisher¿s exact test, logistic regression)
- Survival analysis (Kaplan Meier curves, log-rank test, Cox regression)
- Graphics in Stata
Learning Outcomes
Knowledge
After completion of the course the student should be able to:
- Manage and analyse data in Stata and interpret results from the most basic statistical methods in medical and epidemiological research
Skills
- After completion of the course the student should be able to:
- Merge files and generate new variables
- Import and export datasets from other fil formats
- Use do-files in an efficient manner and write comments to increase readability
- Use help files in Stata to write and edit Stata-code and use do-files to structure statistical analyses in order to achieve reproducible results
- Use descriptive statistics to describe and explore datasets
- Perform statistical analyses in Staa for continuous and categorical variables (including t-test, correlation, linear regression, cross tables with estimation of risk ratios and odds ratios, logistic regression, Kaplan Meier curves, log-rank test, Cox-regression) and understand the interpretation of effect estimates, p-values and confidence intervals
- Choose the correct statistical methods based on formulation of problem statements and type and distribution of outcome and exposure variables
- Make different types of graphs in Stata and edit the graphs to make them ready for publication in scientific journals
Generalized skills
After completion of the course the student should be able to:
- Understand how a typical statistics program works
- Have a basis for starting to use other similar programs
- Understand and interpret analysis results from the most used statistical methods in medical research
- Be able to analyse their own research data with Stata
Level of Study
Semester of Instruction
Required Previous Knowledge
Credit Reduction due to Course Overlap
Access to the Course
Course registration on Studentweb, deadline 1. September for the autumn and 1st February for the spring semester.
Visiting student at the Faculty of Medicine, deadline: 1st August for the autumn semester and 1st January for the spring semester.
Teaching and learning methods
Lectures and individual practices in STATA with help. Home work.
3 days.
Total hours: 15 hours + home work