The pathogenesis of antiepileptic drug (AED) resistance is multifactorial. However, most candidate gene association studies typically assess the effects of candidate genes independently of each other, which is partly because of the limitations of the parametric-statistical methods for detecting the gene-to-gene interactions. A total of 200 patients with drug-resistant epilepsy and 200 patients with drug-responsive epilepsy were genotyped for 3 representative the single nucleotide polymorphisms (SNPs) of the voltage-gated sodium channel genes (SCN1A, SCN1B, and SCN2A) by polymerase chain reaction and direct sequencing analysis. Besides the typical parametric statistical method, a new statistical method (multifactor dimensionality reduction [MDR]) was used to determine whether gene-to-gene interactions increase the risk of AED resistance. None of the individual genotypes or alleles tested in the present study showed a significant association with AED resistance, regardless of their theoretical functional value. With the MDR method, of three possible 2-locus genotype combinations, the combination of SCN2A-PM with SCN1B-PM was the best model for predicting susceptibility to AED resistance, with a p value of 0.0547. MDR, as an analysis paradigm for investigating multi-locus effects in complex disorders, may be a useful statistical method for determining the role of gene-to-gene interactions in the pathogenesis of AED resistance.