This paper introduces a novel framework for analyzing the robustness of survey-based research findings. It integrates Structural Equation Modelling (SEM) with Double Machine Learning (DML) and ordinary least squares (OLS) regression to assess how stable relationships remain across different estimation techniques. The methodology, demonstrated on a FinTech Digital Customer Intimacy model, helps researchers identify which findings are consistently supported and which require more cautious interpretation. AI
IMPACT Provides a more rigorous approach to validating findings in survey-based research, potentially increasing confidence in results derived from machine learning techniques.
RANK_REASON The item is an academic paper detailing a new methodology for statistical analysis. [lever_c_demoted from research: ic=1 ai=0.7]
- Double Machine Learning
- FinTech Digital Customer Intimacy
- Google Colab
- Gradient Boosting
- ordinary least squares (OLS) regression
- Random Forest
- Support Vector Machine
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