Suppose you have a variable X that you would like to predict from a set of predictors P and you want to control for some other variables C. The standard approach is to make a comparison between two models:
% I probably don't have the syntax quite right because I don't use fitlm
% much, but hopefully this will convey the idea:
mdl1 = fitlm(x,C); % predict x from C alone
mdl2 = fitlm(x,[C P]); % predict x from C & P
The improvement of mdl2 over mdl1 (e.g., increase in SSmodel, decrease in SSerror) is then attributed to the predictors in P "controlling for" those in C. For more detail, you might look at Chapter 15 of this online book.
