= Correlated random-intercept and random-slope model
{title2=$Y_{ij}=\beta_0+\beta_1t_{ij}+b_{0i}+b_{1i}t_{ij}+\varepsilon_{ij}$}
A subject-specific <random intercept> and <random slope> may have a joint <bivariate normal distribution> with arbitrary positive-definite <covariance matrix> $D$. With independent <normal> measurement errors of <variance> $\sigma^2$, the marginal <covariance> between a person's readings at $s,t$ is $D_{00}+(s+t)D_{01}+stD_{11}$, plus $\sigma^2$ on the diagonal. Different subjects remain independent. Allowing $D_{01}$ distinguishes this model from an <independent random-intercept and random-slope model>.
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