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Two Continuous Endpoints: The Reduced Fixed Effects ModelIn Chapter 4, we discussed the reduced fixedeffects model for two continuous endpoints. The model can be formulated as:
For the reduced fixedeffect model, triallevel surrogacy is assessed using the coefficient of determination obtained by fitting a linear regression model of the form: where (3® and a® are the trialspecific estimated treatment effects upon Tj and Sij, respectively. The error terms, e®, are normally distributed with mean zero and a constant variance. Individuallevel surrogacy is assessed by the squared correlation between S and T after adjusting for trialspecific treatment effects and is given by: Once the variables specification is complete (see the left panel in Figure 14.1), one can choose the model to be fitted using the command bar in the upper part in Figure 14.1. The Surrogate Shiny App produces a default output shown in Figure 14.2. For the ARMD study, R?_{ndiv} = 0.5318 (0.4315, 0.6321) and Retrial = 0.6585 (0.4695, 0.8476). If other statistics are of interest, one can use the R package Surrogate to produce them. The reduced fixedeffects model specified in (14.1) and in the Surrogate Shiny App in Figure 14.1 is identical to the model fitted using the function BifixedContCont below: Sur<BifixedContCont(Dataset=ARMD, Surr=Diff24, True=Diff52, Treat=Treat, Trial.ID=Center, Pat.ID=Id,Model="Reduced", Weighted=TRUE) 
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