We included in forward and backward stepwise multivariate regression models as covariates all data with p < 0.1 in univariate analysis, with stratification by metformin use.
However, stepwise multivariate regression analysis identified CPB inclusive of cardioplegic arrest as the only predictor of post-operative gastrointestinal complications (OR7.4; CI 3.4 17.9).
The nirK abundance was insignificant in the stepwise multivariate regression models of DEA, although it was significantly correlated to DEA (r = 0.35, P = 0.003) when footslope samples were included in the analysis.
Stepwise multivariate regression (SMR) models of DEA and BD were performed using the measured soil characteristics and denitrifier and nitrifier abundance as explanatory factors to determine whether the microbial community size influenced prediction of denitrification activity.
Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors.
All variables that showed a statistically significant correlation with fecal calprotectin by univariate analysis were subsequently analyzed together in forward and backward stepwise, multivariate regression analyses, after log transformation of fecal calprotectin values.
Analysis of stepwise multivariate regression is reported in Table 2.
β = standardized coefficient as given by stepwise multivariate regression analysis.
In a stepwise multivariate regression analysis, the IMT was used a continuous variable.
A forward stepwise multivariate regression analysis was performed to determine independent predictors of late H/M.
Table 3 summarizes the results of the stepwise multivariate regression analysis for birth weight.
