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In all models, adjustment was done for age, BMI, current smoking (yes vs. no), and physical activity (physically active, regular exercise at least 30 min a week vs. physically less active, occasional exercise, or no exercise).
In these models adjustment was made for BMI and waist hip ratio in categories to avoid having to make assumptions about the linearity of their associations with the outcomes.
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The model adjustment was conducted by solving the inverse problem of parameter estimation for appropriate equipment properties using a total power dissipation of 4.8 kW in the PEBB.
In this model, adjustment was made for 11 variables.
In the first multivariate model, adjustment was performed for age, sex and centre of inclusion.
Although most trials that we evaluated were registered, the information regarding statistical analyses, specifically model adjustment, was rarely provided.
In an alternative model, adjustment was made for the occurrence of glucose values ≤ 4.7 mmol/l, which is also independently associated with mortality [ 3, 30].
When the effects of age and sex on implant survival were analyzed with the Cox model, adjustment was also made for implant groups (Furnes et al. 2001).
In multivariate model, adjustment was done for age, height, weight, sex, smoking status, spoken dialect, education, socio-economic status (SES) and arsenic levels in drinking water.
Information on analysis plan regarding model adjustment was available in 6% (9/162) of trial registry entries, 78% (21/27) of design papers, and 74% (40/54) of protocols obtained from authors.
In line with the requirements of additive-regression models, adjustments were forced for recipient gender and age and transplantation period.
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