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Unmeasured or imprecisely measured confounders will produce residual confounding and limit the validity of multivariate analysis.
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Linear regression analyses are used to analyze the association between overweight and number of GP consultations (question 3) These analyses will be adjusted for measured confounders.
Unlike randomized trials, observational studies do not control treatment allocation, and statistical models are used to adjust for measured confounders.
7 9 As we may have been unable to fully account for frailty, which has been defined in recent studies, 36 37 we will use estimates from published data to model this unmeasured (or inadequately measured) confounder in a sensitivity analysis.
Possible confounders will be entered into the regression analyses.
Potential confounders will serve as covariates where appropriate.
Data on all known potential confounders will be obtained.
Any confounders will be included in remaining analyses.
Potential confounders will be included as covariates, if indicated.
To control for potential bias, possible confounders will be included in all further analyses.
By randomising patients, possible confounders will be distributed randomly over the groups.
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