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Two logistic regression models, one for each social support construct, were used to conduct multivariable analyses.
We cannot exclude the possibility that these were chance findings, since the statistical power to conduct multivariable analyses may have been inadequate.
Also, due to the small sample size among MSM's, opportunities to determine recent MSM behavior (i.e. last 3 months) and conduct multivariable analyses were not possible.
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We conducted multivariable analyses adjusting for previously identified risk factors for individual ischemic placental diseases.
For fathers, we additionally conducted multivariable analyses of blood pressure, BMI, serum lipids and glucose with pregnancy length.
Before conducting multivariable analyses we used the variance inflation factor (VIF) in order to control for possible multicollinearity effects.
In the case of papers that conducted multivariable analyses, however, inverse and positive relationships were observed in 51.1 and 1.1%% of cases, respectively.
To further confirm these results, we also conducted multivariable analyses on the entire study sample, including the confounding variables and the variable "anemia yes/no".
We felt that the role of depression specifically as a potential confounder of the relationship between SES and the outcomes of interest was less clear and we therefore conducted multivariable analyses both with and without adjustment by MHI-5.
Second, we conducted multivariable analyses using consecutively the region of medical school and the region of specialty training as the dependent variables and the demographic characteristics as the independent variables.
To evaluate potential modifying effects of gender, BMI (<30, ≥30), treatment method (chemotherapy/radiation vs. no chemotherapy/radiation), and years since diagnosis (before 2000 vs. 2000 or later) on the association of PFAA levels (in quartiles) to history of CRC, we conducted multivariable analyses stratified by each potential effect modifier.
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