How can I group several variables into 1 variable of interest? I have a survey data and there are 2 questions (variables from the data at the same time and Likert scaled) that I would like to group them together in 1 variable. This is also, my one dependent variable. I would like to do the same with the second dependent variable and then do a regression analysis. For e.g. two questions are giving the same end interpretation = Internal sources of financing.
Does anyone have an idea how can I do this? I am doing my analysis in R.
Thanks.

So multicollinearity is only a major problem if the correlations are at least 0.9.
Factor analysis will show how the independent variables are related to each other.
PCA is similar, you can see how the variables are related to each other based on the scores, and then for each observation compute the PC score.  So if you select the first two components then you'll have two scores for each observation.  You can then use those in the regression analysis.
With only four variables not sure if this approach makes a lot of sense.  For example if the correlation between Q1 and Q3 is 0.999 then you're not going to be able to separate these effects.  However, you do know the Q1 and Q3 are measuring the same underlying construct.  You can run separate regressions and interpret from there.
Hard to really say what to do without seeing the data and what the research questions are but hopefully this provides some ideas.
