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In randomised trials, it is important to be able to adjust for covariates to gain precision in estimating the mean cost.
To adjust for differences in the precision of the smoothed SLA-specific estimates, the inverse of the variance was used to weight the dichotomous SIR variable.
To adjust for each situation, metrics such as precision or overhead can be re-defined on the basis of uniquely curated items or by using novelty as a factor in the assignation of value.
Analytic models of intervention effect will include adjustments for individual-level demographic and background variables, such as age, education, and socioeconomic status, measured at baseline prior to randomization to examine for improved precision and to adjust for any (random) covariate imbalance across groups [ 57].
Standard errors were obtained as above to adjust for the effects of weighting on the precision of estimates.
Because we will be using analyses of covariance to adjust for baseline, we expect to have greater precision and power than indicated here.
Because we will use analysis of covariance to adjust for baseline values, we expect to have adequate precision and power.
When the precision estimate test was used to adjust for publication bias, the overall OR was altered to 0.79 (95% CI 0.58 1.07).
When a precision estimate test was used to adjust for publication bias the effect of statin treatment was no longer significant, with an OR of 0.79 (95% CI 0.58 1.07).
The m-CCI enabled us to adjust for underlying diseases, and the large study size provided statistical precision for the estimates.
Baseline values will be incorporated in these analyses to adjust for any imbalance at baseline despite randomization and to increase precision by removing between-person variability.
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