Comparing Weighting Schemes in Modeling Child Malnutrition in East Java
Abstract
Partial Least Squares is increasingly used as an alternative to covariance-based SEM due to its flexibility in handling non-normal data, small sample sizes, and complex models, as well as its ability to operate under different inner weighting schemes. However, empirical studies rarely compare these weighting schemes, even though they may influence measurement validity and structural interpretations. This study applies PLS-SEM using both the path and factor weighting schemes to evaluate their performance in modeling child malnutrition. Child malnutrition remains a major public health concern, as it is driven by the interaction of socioeconomic, food security, parenting, and access to basic services. The study estimates and evaluates measurement and structural models using PLS under path and factor schemes. The findings show that both schemes produce acceptable measurement and structural models, but the path scheme yields more consistent indicator significance and more stable structural relationships, while the factor scheme is more sensitive to weaker indicators, leading to some nonsignificant loadings and paths. The results suggest that although both weighting schemes are suitable for exploratory analysis, the path weighting scheme provides more robust and interpretable results for explaining child malnutrition, highlighting the importance of weighting scheme selection in applied PLS-SEM research.
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