Data Processing and Statistical Methods in Occupational Stress Research

Occupational stress has been a hot spot in occupational health research. However, the mistakes and defects in research data processing and statistical analysis by domestic researchers have adversely affected the results presented in a correct and scientific manner, and derogated study performance. With regard to the above mentioned aspects, this article introduced common data processing methods including: handling missing variables in questionnaire data and marginal values of category determined by scoring; considerations in norm application; data distribution characteristics; and the key points of statistical methods including correlation analysis, matched data analysis, analysis of covariance, hierarchical multiple linear regression analysis, logistic regression analysis, and structural equation modeling.