Pairwise Kruskall-Wallis post hoc analyses were performed to determine which variables differed significantly from each other, stratified for the different drinking categories.
Multiple univariate statistical testing across the SC and 2, 20, and 200 μg/L fenitrothion treatment groups revealed 9.34% and 5.84% of the variables in the NMR and DIMS liver data sets were significantly different (FDR < 10%), respectively, while 0%andd 1.56% of the variables differed significantly in the NMR and DIMS testes data sets, respectively (Table S7, Supporting Information).
Nine meteorological variables differed significantly.
Four vegetation variables differed significantly among the 2D complexity groups: the standard deviation of the Enhanced Vegetation Index, the coefficient of variation of density per transect (CV density), mean tree diameter (DBH), and foliage height diversity (FHD).
Distribution of many variables differed significantly (p < 0.05); therefore, relationships between biological data (abundance of autotrophic nanoplankton, heterotrophic nanoplankton, and microzooplankton) and various environmental variables (water temperature, temperature, NH4 +, DIP, and urea) were determined using Spearman's rank correlations analysis (Zar 1999).
None of these variables differed significantly between men and women.
Within the discovery set of subjects, four demographic variables differed significantly in AA versus CAU subjects: lower smoking pack years and hematocrit levels, and higher occurrence of hypertension and fructosamine levels (Table 1).
Importantly, none of these variables differed significantly.
All of the variables differed significantly between the two groups.
All variables differed significantly between the two groups.
