How do I derive a rating from two variables containing zeros?

Question

I have a dataset of the performance of probands in an experiment. An observer watching the performance noted positive and negative performance remarks on a simple tally, and ended up with something like

Proband ID  Positive Remarks  Negative Remarks
         1                 5                 2
         2                12                 8
         3                 6                 0

(assuming that each remark has equal weight.)

I would like to rate probands based on a combination of positive and negative remarks to be able to state a mean / median performance, to check for peculiar deviations and outliers, and to ultimately test for dependencies on other variables.

Intuitively, I would use a simple relation of Positive Remarks / Negative Remarks. Eyeballing this looks promising, but there are lots of zeros in the negative remarks.

How could I combine these variables into a single performance rating preferrably expressing the relation of positive to negative remarks in the presence of zeros?

I have checked related questions:

• "How do I order or rank a set of experts?" points to Keeney & Raiffa which I will at some point look into, but maybe there is a quicker answer.
• "How do I combine two related variables into one?" is somewhat related, but has been closed as unclear.

Answer 1

A simple metric that could work for a problem like this is:

Scaled = P/(P+N)

Anything that is purely positive will get the score 1. Anything that is purely negative will get the score 0. Equal P & N gets 1/2. It ignores the length of the vector. Along the lines of what was suggested by @sean507, this is just the proportion of all answers that are positive.