A simple overview in four steps
- This is what it they look like:
- Good for:
- Demonstrating differing survival (or event free survival) curves given different baseline characteristics. Example: to compare survival between patients on a new drug ( blue above ) with no drug ( red above ) or survival in people with one disease vs no disease (or a different stage of disease).
- Takes into account different lengths of follow up and loss to weekly buy viagra using paypal follow up.
- Easy for medics to understand (we are simple people) as it is a nice visual way of showing the data.
- Not good for:
- It doesn’t control for confounding factors (if one group has different demographics than another) – if this is the case perhaps consider a Cox Regression analysis.
- This is how to do it in SPSS and R:
Written by: Dr A.P. McGovern