Now we will discuss parametric versus non-parametric tests.
The main type of survival analysis methodologies can be classified as parametric or non-parametric. Across statistical analysis, users would come across both these types of tests and models. While non-parametric approaches have their benefits, in practice parametric tests are used more in the financial world.
Parametric tests assume that the data follows some distribution. For instance, this is one of the critical conditions of regression. Parametric tests in some instances have a greater statistical significance. They can also perform quite well if the spread of two or more groups being compared is quite different. If survival times of two or more industry groups are quite different then a parametric test might be more useful for comparison. The biggest drawback of the parametric test...
