Your help will be kindly appreciated .

- Thread starter siyareigner
- Start date
- Tags #multiple regression plots

Your help will be kindly appreciated .

You could well start with bivariate descriptions and graphs to see what's going on. Is "expression protein" a contiuous variable, or what is it?

With kind regards

Karabiner

You could well start with bivariate descriptions and graphs to see what's going on. Is "expression protein" a contiuous variable, or what is it?

With kind regards

Karabiner

Thank you for your reply!

if you want to use it in regression. So you'll soon have two or three dozens of

predictors in your model, and only 94 observations. Therefore you should perform

a pre-selection of characteristics to be used in the multiple regression(s). The pre-

selection should preferably be based on substantial considerations (theoretical

or practical interest), not on statistcal pre-tests.

With kind regards

Karabiner

Thank you.

Best regards

so I should first do maybe a visual test or correlation test to see if there is any correlation and then take only these variables that are interesting into my regression?

but on theoretical and/or practical considerations.

Another question, is it ok if my data for tissue type are arranged like this in the column: normal, tumor, normal, tumor for every patient thus 2 values? Or is it better to split my protein expression variable into two variables, such as protein expression for normal tissue and protein expression for tumor tissue? Then I don't need to have patient ID twice every time in my column and also Tissue type variable is no longer needed.

you perform, and how familiar you are with both of them.

With kind regards

Karabiner