A comparison of the different multivariate analyses, with exclusion or inclusion of most of our variables, did not change our results.
Multiple regression analysis is appropriate for multivariate analyses with a continuous outcome variable.
The outcome differences remained robust in multivariate analyses with controls for demographic factors of age, gender, education, food security, and job category.
To identify fishes that might serve as native biological control agents for schistosomiasis in the lower Senegal River basin-one of the highest transmission areas for human schistosomiasis globally-we surveyed the freshwater fish that inhabit shallow, nearshore habitats and conducted multivariate analyses with quantitative diet data for each of the fish species encountered.
Because a complete set of vital signs was not consistently documented at participating hospitals, records with data missing for respiratory rate (RR), blood pressure (BP), or heart rate (HR) were included in multivariate analyses with absent values assumed normal.
In multivariate analyses with updated exposure, women with the highest levels of depressive symptoms had an elevated risk of incident colorectal cancer (hazard ratio = 1.43, 95% confidence interval: 0.97, 2.11) compared with women with the lowest levels of symptoms (p trend) = 0.04).
Therefore we performed subsequent multivariate analyses with combined data (Table 5 and Table 6), in attempt to strengthen the statistical power.
Although the proposed test was applicable to multivariate analyses with arbitrary number of traits, we only considered bivariate situations for simplicity.
The clinical parameters were analyzed by univariate and multivariate analyses, with pCR as the dependent variable.
Statistical analyses included univariate and multivariate analyses with conditional logistic regression.
Ovarian cancer risk perception was also included in the multivariate analyses with p = 0.15.
