Abstract: In the 50 years since Rubin causal model was introduced,significant progress has been made in the theoretical understanding and analytical methods of causality,leading to a marked increase in empirical research using causal inference methods.Despite these achievements,the model faces various challenges and limitations.One such limitation is its inability to ensure the random assignment assumption when applied to observational studies.Furthermore,the model overlooks the substantive importance of the research problem in its pursuit of satisfying the criterion of approximate random assignment.In addition,the model is deficient in analyzing the causes of effects and identifying causal mechanisms.To address these challenges,researchers must not only enhance the quantitative research design but also conscientiously integrate and learn from qualitative analysis tools.This organic combination of qualitative and quantitative methods is imperative for conducting thorough and comprehensive analyses of causality.