Application of Factorial Experiments in Health Data Analysis: Exploring Interactions and the Impact of Factors on Clinical Outcomes
DOI:
https://doi.org/10.29304/jqcsm.2025.17.42531Keywords:
Factorial Experiments, Type 2 diabetes, HbA1c,Simple effectsAbstract
This paper will use a 2x2x2 factorial experiment design to evaluate the impacts and interactions of type of treatment, diet, and exercise activities on glycated hemoglobin (HbA1c) in subjects who have type 2 diabetes. Factorial ANOVA, simple effects Analysis, and Tukey post hoc test were used to analyze the data of 240 participants. The Marginal Means (EMM) were calculated to correct the imbalanced data.
The findings showed that all factors had significant main effects (p < 0.001) and large-scale two-way interactions. The simple effects analysis revealed that only under low physical activity, the interaction between treatment and diet was significant, which means that dietary change increases the effectiveness of drugs in sedentary patients. Factorial model explicated approximately 95 percent of the variance in change of HbA1c justifying the excellent position of integrated therapeutic and lifestyle interventions in glycemic regulation
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Copyright (c) 2025 Wisam Wadullah Saleem
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