Exploring the Causal Complexity in Mate Preference:A Reanalysis of Survey Experiment Data Using QCA
This paper uses two methods—fixed effect model and fuzzy-set QCA(Qualitative Comparative Analysis)—to analyze the survey experiment data on mate preference from the CGSS 2021.The study reveals that while the conclusions of both methods were consistent,QCA has been proved to be more advantageous in capturing the complexity in mate preference.Specifically,the influence of mate selection conditions on mate selection decision is not isolated,but bound together,leading to configurational features in nature.In addition,acceptance and rejection decisions are affected by different causal mechanisms,and regression analysis cannot study the asymmetry of this causal relationship.QCA and regression models are apt for analyzing different causal questions.It is only through the complementary use of both methods that a synergistic effect can be achieved.