The more I read statistics, the more I don’t know!

During my time as a medical student (in early 90′s, t-test & chi-square are already the most sophisticated statistical tests on earth. People don’t even bother to run One-way ANOVA to compare variances of 3 or more means. Then I learn about regression. My MPH thesis was using survival analysis. Yup, those with cox-regression. That time I already know about GLM (General Linear Model), which is a group of procedures that utilise t-test, ANOVA, regression and the like) where observations are independent and fixed. What if the dependent variable still continuous but the there are correlation between independent variables? That’s when Linear Mixed Model (LMM) come into the picture.

The most important thing to know is the hierarchical model. What is hierarchical effect? If you understand linear regression, it will be easy for you to understand hierarchical modelling or multi-level analysis. Linear regression analyses effects at one single level. What is level?

To be continue….