Contribution plots are important to identify the unusual process variables for fault isolation. In this paper a unified method calculating contributions is presented. Principal component analysis based process monitoring is first analyzed and variable contributions to monitoring statistic T2 and Q are modified to bring a unified framework for contribution calculation. Then this method is generalized to other statistical process monitoring methods such as canonical variate analysis, independent component analysis and kernel principal component analysis. Some issues, including negative contribution and confidence limit, are discussed and relative contribution is introduced to give a more reasonable explanation on variable contribution. Simulations on a continuous stirred tank reactor system and the Tennessee Eastman benchmark process are performed to show the proposed method is effective to isolate fault variables.