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The Full MixedEffects ModelThe full mixedeffects model, discussed in Chapter 4, is a joint model for the surrogate and true endpoint given by
Here, and are fixed intercepts, a and в are the fixed treatment effects on the two endpoints, m_{Si} and m_{Ti} are random intercepts, and a* and b_{i} are trialspecific random treatment effects. As pointed out in Chapter 4, the vector of random effects (m_{Si}, m_{Ti}, a_{i},b_{i}) is assumed to follow a normal distribution with zero mean and covariance matrix (4.2). The error terms, ?_{Si}j and ?_{Ti}j, are assumed to follow a bivariate normal distribution with covariance matrix FIGURE 12.11 Error terms covariance matrix. FIGURE 12.12 Error terms covariance matrix. given in (4.3). Trial and individuallevel surrogacy can be estimated using the variancecovariance elements in the covariance matrices (4.2) and (4.3), respectively. For more detail, see Chapter 4. The SAS Macro %CONTRANFULLThe %CONTRANFULL macro can be used to perform the analysis and it can be invoked using the following call: %CONTRANFULL(data=simdata,true=true,surrog=surr,trt=treat, trial=trial,patid=patientId,looa=1). The macro’s arguments are the same as those presented in Section 12.2. 
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