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Polarity-coincidence correlation (PCC) is usually analyzed under the assumption of independent noise inputs and small input-signal power. Thus, the difficulty of evaluating the variance of the PCC statistics for inputs with arbitrary cross correlations is avoided. Recently, a series expansion method was considered to obtain a variance expression for a strong Markovian signal that is added to two independent white-noise inputs and for a small Markovian signal added to two dependent Markovian noise inputs. The series expansion method converges slowly and requires six joint summations with infinite limits, so that some alternative approach is desirable. Our objective is to compute the variance of the PCC statistic by an alternative method for the above mentioned examples.