I have a table which contains about 80 variables. I will give one variable as input and as output I want to have all the variables that are related to the input variable.
Example: I have hospital data which contains variables such as patient name, blood pressure, sugar, heart rate, ECG, "heart patient" (binary yes/no variable), etc. If I give "heart patient" as input, then as output I would get ECG, heart rate, blood pressure, etc.
So I need to find variables which are related to the "heart patient". And the rest will be ignored.
I am using principle component analysis (PCA) to solve this. The problem is that PCA gives me the number of variables which best represent the data set, not the variables that are related to a given variable.
Please suggest me some idea or keywords that help me to proceed. Also, could you give me some reading which would improve my PCA understanding. I have already read Making sense of principal component analysis, eigenvectors & eigenvalues.