What are the classifications of medical statistical correction models?

The classification of medical statistical correction models includes the following contents:

1, linear regression model: using linear relationship to correct medical statistical data can correct some linear deviations or errors.

2.Logistic regression model: used to correct the statistical data of dual medicine, such as judging whether there is a certain disease or adverse event.

3. Linear mixed effect model: it is suitable for correcting medical statistical data with fixed effect and random effect, and can consider individual differences and group characteristics.

4.SUR model: dealing with multiple medical statistical indicators with related structures and solving multiple correction problems and correlation problems.

6. Deep learning model: Using neural network model to process medical statistical data can capture features and modify data flexibly.