Objective: The aim of this study is to evaluate the effectiveness and efficiency of causal links between various error causes in human error analysis. Background: As finding root causes of human error in safety-critical systems is often a cognitively demanding and time-consuming task, it is particularly necessary to develop a method for improving both the quality and efficiency of the task. Although a few methods such as CREAM have suggested causal linking between error causes as a means to enhance the quality and efficiency of human error analysis, no published research to date has evaluated the performance of the causal links. Method: The performance of the CREAM links between error causes were evaluated with 80 railway accident investigation reports from the UK. From each report, errorneous actions of operators were derived, and for each error, candidate causes were found by following the predefined links. Two measures, coverage and selectivity, were used to evaluate the effectiveness and efficiency of the links, respectively. Results: On average, 96% of error causes actually included in the accident reports were found by following the causal links, and among the total of 121 possible error causes, the number of error causes to be examined further was reduced to one-tenth on average. As an additional result of this work, frequent error causes and frequently used links are provided. Conclusion: This result implies that the predefined causal links between error causes can significantly reduce the time and effort required to find the multiple levels of error causes and their causal relations without losing the quality of the results. Application: The CREAM links can be applied to human error analysis in any industry with minor modifications.