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We distinguish models 2 and 3 for two reasons: firstly, because we want to estimate the total net relationship between education and skills, which is achieved by model 2, where entering variables on the causal path from education to skills (like in model 3) would introduce overcontrol bias (Elwert and Winship 2013).
Multiple linear regression analyses were conducted entering variables simultaneously into the model.
The potential confounding effect of the variables was assessed by entering variables one at a time in the models.
We performed a multivariate analysis of risk factors for ASB entering variables that had a p ≤0.1 in univariate analysis.
Statistical limits for removing and entering variables from the stepwise model were P = 0.10 and P = 0.05, respectively.
Then adjusted analysis was performed by entering variables that have shown significance during univariate analysis or have been previously reported to be significant in other literatures.
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A window will appear with prompts to enter variables into either the CATEGORICAL VARIABLES space or the QUANTITATIVE VARIABLES space.
Confounding was assessed by taking out and re-entering variables into the final models one by one and check for biologically important changes of estimates.
Only entered variables shown.
We entered variables using the manual stepwise (forward-backward) method.
Entered variables were dropped if they were no longer significant when other variables were added.
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