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Note that extended models including baseline covariates should lead to greater statistical power under both scenarios.
Analysis of quantitative secondary outcome measures will use linear mixed models including baseline covariates and random effects for therapy group [ 52].
The improved performance of models including baseline HR-QoL - still not explaining more than 40% of variability - relates to the fact that patients with low baseline HR-QoL have a better chance for improvement.
In the remainder of this section the mathematical models for binary and continuous outcome measures are described beginning with simple meta-analytic models which are then extended to MTC models including baseline characteristics and other assumptions necessary for the RA model.
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ANCOVA models included baseline PRO score and treatment group.
The models included baseline, treatment, investigator, subgroup, and treatment-by-subgroup interaction.
The models included baseline QoL, age, education (primary, secondary and tertiary), weight change and use of hormone replacement therapy (HRT).
Selected multivariable models included baseline periodontal status as a covariable for the prediction of 5-year periodontal change.
Models included baseline height and weight, age, and BMD of the femoral neck from year 5 if available, otherwise at baseline.
A clear baseline effect was observed for both QTcF and heart rate, and the final models included baseline as a significant covariate on the estimate of the intercept (Table 5).
A series of linear regression models was performed in which average change in total spiral score per year was the dependent variable, and independent variables in different models included baseline demographic and clinical characteristics.
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