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Since perceived social support was predicted by orphanhood groups, the fourth step we conducted adjusted multivariate linear analyses (adjusted models).
The Bonferroni method was used for multiple testing adjustment of the p-values obtained from the 18 paired t-tests conducted; adjusted p-values of p ≤ 0.05 can be interpreted as statistically significant test results.
We also collected data on important variables and confounders, and conducted adjusted analyses to assess the impact on the results.
The association analyses were conducted adjusted for relatedness between subjects, as described earlier.
Longitudinal regression using weight as response value and physical activity as predictor value was conducted, adjusted for baseline covariates.
Using SPSS software (version 4.0; SPSS Inc., Chicago, IL), we conducted adjusted analyses by use of analysis of covariance between the cumulative lead exposure groups.
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Unadjusted and age-adjusted prevalence and simple and multiple logistic regression analyses were conducted, adjusting for several potential confounders (BMI, alcohol drinking, smoking, physical activity, and sociodemographic characteristics) and survey design.
Conditional logistic analyses were conducted adjusting for social class, ethnicity, tobacco and alcohol habits.
Based on the results of the univariate analyses, multivariate analysis was conducted adjusting headache time duration, headache intensity, and no aggravation by routine activity (Table 3).
Next, a rectangular-completing algorithm of ROIs is conducted, adjusting ROI with irregular shape to a rectangle (Figure 5). Figure 5 The schematic diagram of rectangular completing.
A sensitivity analysis was also conducted adjusting for several potential confounders.
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